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Nimra Iffat, Muhammad Shahzad Chaudhry and Asma Riaz

_______________________________________________________________________________

155

Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry

(A Case Study of Pepsi Co. Pakistan)

_______________________________________________________________________________

ISSN 1684-8403

Journal of Statistics

Volume 24, 2017. pp. 154-164

________________________________________________________________________

Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry

(A Case Study of Pepsi Co. Pakistan)

Nimra Iffat 1, Muhammad Shahzad Chaudhry2 and Asma Riaz 3

Abstract

This study investigates the impact and usage of business intelligence on the quality decision making from two usage perspectives; employee designation and departmental classification. Study has been done on Pepsi Cola International Private Limited as a case of beverages industry of Pakistan. After a decade of reforming policies and development, Fast Moving Consumer Goods organizations are now playing vital role in the development and sustainability of economy in Pakistan. A single exploratory case study approach has been employed to analyze the Pepsi Co. by using quantitative method. Pepsi Co. organization is using business intelligence technology to twirl the raw data into useful information, resultant information into knowledge and plans that are optimizing business strategic activities such as decision making and improve the proactive management, curtail expenditure and capitalize the profit. For the collection of data, questionnaire survey was conducted. Based on respondents, stated association between significance of business intelligence in organization on basis of department and employee classification on quality decision making through analytic hierarchy process has been testified with Regression analysis and Sobel test.

Keywords

Strategic decision making, Multinational organization, Fast moving consumer goods, Analytic hierarchy process

______________________________

1 Department of Statistics, University of the Punjab, Lahore, Pakistan.

Email: [email protected]

2 Department of Statistics, GC University Lahore, Pakistan

Email; [email protected]

3 Department of Statistics, National College of Business Administration and Economics, DHA

Campus, Lahore, Pakistan.

Email: [email protected]

1. Introduction

Organizational internal environment build up unusual forces from diverse kind of factors associated with the organizational financial functionality such as its structure, processes, people, systems and resource constraints. All these forces, their nature, functionality, controllability can be understood and well organized with the use of Business Intelligence (BI). So we can say that BI is an implausible tool which every nature of business required in order to gain competitive advantage as well as to contend in a vibrant, complicated and competitive business environment. BI significantly provides strategic insight for the adaptability, changeability and applicability of management toward organizational maximum profitability. BI let a business to forecast and conjecture the economic situation by visualizing data in a way that can be infer at strategic level. With help of data extracted through it, decision making is done on basis of priority and criterion that indicates how many times more important or dominant one element is over another element. And in our opinion organizational intelligence environment concede by human brains but with BI tools and techniques (Duedahl et al., 2005).

Beverage industries are playing key role in establishing the Pakistan economy. It has developed over a hefty level growth periodically. It has twelve-monthly intensification of approximately 20% to 25% and has the impending ability to twice its volume in next 3 to 5 years. These organizations employed the majority of workers; which augment the economic growth of country. So, this diligence along with large number of market network together with shops and outlets are the reason to prop up and to spawn ample extended economic activity in Pakistan. Thus it is generally recognized as significant to economic enlargement and growth. In an environment where consumer satisfaction is key for any business to survive and develop, consumers focused organizations be obliged to be competent to congregate demand and service requirements timely, according to expectations and as efficiently as promising.

BI tool philosophy straight away relate to what these companies are struggling to attain. With BI system these organizations were competent to change its business operations towards their object of customer focus. It endow with a next-generation software solution supporting the direct store delivery process from order to cash and settlement. The BI system will support the existing processes to improve it and endow with new functionalities and opportunities to perk up their customer service and contentment. It also helps to develop merchandising, permits for growth in marketplace share, amplifies customer satisfaction, and diminishes logistics cost (Hagel and Brown, 2001). The current purpose of study is to find out the significance of BI and its impact on Fast Moving Consumer Goods (FMCG) Industry in Pakistan.

2. Literature review

Organizations in history faced a lot of snags. Manual record of transaction, manipulation of data, report formation over computerized system escorted to many dilemmas such as; inaccuracy, less reliable, repetition of data, lack of internal control, loss of time, paper damaged and system crash etc. 1n 1940 computer were used for organizational clerical activities. Financial record is always use as a tool to measure and evaluate the firm’s position. Intelligence is an amalgamation of analysis, assessment, and interpretation of information according to the particular difficulties that this may entails to endow organizations with a cutthroat strategy to compete in the market and be profitable at the same time. BI Tasks includes forecast future with the past and present performance and what if’ analysis of impact of changes and alternative scenarios (Armstrong et al., 2013).

Buckhout et al., (1999) described that decision making system is all about allocating and using source of funds in appropriate manner. It is associated with hoisting the capital desired to invest in the enterprise’s assets and activities, the right speculation of the inadequate and limited finance between challenging uses, and to make certain that the assets are being exploit efficiently and proficiently in attaining the enterprise’s objective. However, according to Bacon (1992); “decision making includes all areas of management, financial implications of investment, production”.

Rapidly increasing trend of growth is always a characteristic of highly developed and contemporary organizations. More sales intensify more rapidly demand for capital intrudes along with increase in stock as well as receivables. So, functionality of decision making strategy is lie in expounding the strategy for financing, defining down financing objectives, setting up the on the whole scale, conduit and productive and profitable techniques of financing, arranging deliberate methods of capital structure optimization and lastly envisage and amass the amount of capital the organization required (Chen et al., 2012).

To compete in the highly completive advantage the most significant strategy is to understand and keep track record of all data which is created in result of day to day operations for future events. BI is not merely a technology but it is a methodology. With the usage of BI organization can understand in better way growth in systematic sale level, guide trade policies, required capital, increase level of stock in response to elevated ratio of receivables, making strategies for allocation of resources, investment policies and reinvestment to attract new products, sustain old one with value adding features in existing products (Apte et al., 2003).

BI conduits amongst different departmental activities for the purpose to attain information regarding day to day operations to make working capital management efficient, allowing FMCG industries to scrutinize the business performance. With BI these industries can amalgamate influential tools, scrutiny, consistent reporting, controlling system with an assortment of key performance indicators (KPIs), data assimilation, among other features, within a service-oriented architecture vital for a superior business administration to guide managers in strategic direction for quality information, with the establishment of principles, values and procedures to make certain compliance with the objectives (Rajteric, 2010).

For decision making comparisons is done to indicate which element has to execute before on basis of significance how many times more important or dominant one element is over another element with respect to the criterion or property with respect to which they are compared. For example, one compares a drink indicated on the left with another indicated at the top and answers the question: How many times more, or how strongly more is that drink consumed in the US than the one at the top? One then enters the number from the scale that is appropriate for the judgment: for example enter 9 in the (coffee, wine) position meaning that coffee consumption is 9 times wine consumption. These strategies are used to make effective decision making by using the data of software and hierarchy process (Byun, 2001).

Cross sectional analysis of firm’s performances is facilitated when enterprises has a repository consist of consolidated, unstructured and semi structured data from finance, marketing, production, human resource, customer service and other departments including external sources data, led to scrutinize exploratory analysis using BI methodologies (Mohammad, 2012). Combination of informative historical data with BI facilitates to craft strategic decisions (investment, financing, profit distribution and customer retaining etc.) through potentiating patterns to understand the business processes. FMCG should espouse a deliberate and dynamic code of conduct, fulfilling the demand of customer by balancing supply and maintain capital, R & D development on exploring more competitive pricing model, catering the new market by sustain with the old one and gaining the cutthroat position in market.

Use of BI with cloud will be very constructive and profitable for every organization. Cloud BI is a new way to do BI. Instead of installing complex and expensive software BI will run in cloud. There is no need to install or buy any hardware. When organization computing need will grow with the passage of time cloud will automatically assign new resources. That’s what makes cloud BI more powerful tool.

Chaudhry et al., (2016) investigated the critical failure factors and significance of business intelligence system on decision making in Pakistan. Only 2 percent SMEs applying BI framework for their elementary leadership others are using diverse sort of gadgets for the feasible administration.

3. Research objectives and research questions

Today due to increase in demand, BI became an indispensable issue in business world to perk up the Business progression and development. In FMCG industries there is large amount of data to be used. Mangers need right information at the right time on right place to make productive and profitable decisions. The objectives were formulated as follows:

· To find out the BI important for an organizational quality decision making

· To find out the BI role to upsurge the organizational efficiency and effectiveness?

Research objectives defined above leads to following objectives:

· What is the significance of BI in organization on basis of department and employee classification on quality decision making through analytic hierarchy process?

· Has BI helped organization to align organizational performance with pre-set goals?

The following research hypotheses are made to meet the research objectives:

· H1: There is significant relationship between BI used in organization on basis of department and employee classification and quality decision making through analytic hierarchy process.

· H2: There is significant relationship between BI and quality decision making by employee through analytic hierarchy process.

4. Theoretical framework

Figures 1 is showing the mediation of analytic hierarchy process between the business intelligence system and strategic decision making system. The following linear models are used to test this mediation.

Model 1: Estimating strategic decision making (SDM) system from business intelligence system (BIS):

SDM = im1 + c BIS+ em1 (4.1)

Model 2: Estimating analytic hierarchy process (AHP) from business intelligence:

AHP = im2 + a BIS + em2 (4.2)

Model 3: Estimating strategic decision making from both business intelligence system and analytic hierarchy process:

SDM = im3 + c BIS + b AHP + em3 (4.3)

The direct effect of BIS on SDM is: c

The indirect effect of BIS on SDM through AHP is: a * b

The total effect of BIS on SDM is: c = c + a * b

5. Research methodology

The research consists of quantitative techniques to analyze the relationship between BI system and strategic decision making system. SPSS is used for the Regression analysis and Sobel test. Case from beverage industry is taken under consideration. Questionnaire is used to collect the data from employees of organization. One hundred respondents participate in this research. The questionnaire is designed to collect information pertaining to demographic of respondents and company, BI usage level and relation of BI with decision making.

6. Data analysis and interpretations

6.1 Significance of business intelligence system (BIS) in organization on basis of department classification on quality decision making (QDM) through analytic hierarchy process (AHP):

Run Regression IV(BIS) predicting DV(QDM): In Table 1, based on the Regression result, the p-value in ANOVA is 0.007, therefore, there is significant relationship between business intelligence in organizational department and quality decision making. The value of use of BI department wise is the total effect: c = 0.380 which is highly significant.

Run Regression IV(BIS) predicting MV(AHP): In Table 2, based on the Regression result, the p-value in ANOVA is 0.001 so there is significant relationship between business intelligence in organizational department and analytic hierarchy process. The effect of BIS on AHP is a = 0.306 which is highly significant.

Run Regression IV(BIS) and MV(AHP) predicting DV(QDM): In Table 3, after analyzing the values associated with AHP, the effect of quality decision making appears to be small (c =.268 with AHP; c = .380 without AHP, that is, c < c). Thus, there is support for partial mediation. Now, Sobel test is used to determine whether there is significant partial mediation. Preacher and Leonardelli (2017) online Calculation for the Sobel test has been shown in Table 4. The Sobel test P value is less than 0.05. Thus, the analytic hierarchy process is a statistically significant partial mediator of the effect of business intelligence on quality decision making on organizational departmental level in beverage industry in Pakistan.

6.2 Significance of business intelligence on quality decision making by employee through analytic hierarchy process:

Run Regression IV(BIS) predicting DV(QDM): In Table 5, based on the Regression result, the p-value in ANOVA is 0.002 therefore, there is significant relationship between business intelligence in organizational department and quality decision making. The value of use of BI employee wise is the total effect: c = 0.377 which is highly significant.

Run Regression IV(BIS) predicting MV(AHP): In Table 6, based on the regression result, the P-value in ANOVA is 0.000, so there is significant relationship between business intelligence in organizational department and analytic hierarchy process. The effect of BIS on AHP is a = 0.374 which is highly significant.

Run Regression IV and MV predicting DV: In Table 7, after analyzing the value associated with AHP, the effect of Quality decision making appears to be small (.377 without AHP; .259 with AHP).Thus, there is support for partial mediation. Now, Sobel test is used to determine whether there is significant partial mediation to see reduction of .118 (.377 to .259). Preacher and Leonardelli (2017) online Calculation for the Sobel test has been shown in Table 8. The Sobel test P value is less than 0.05. Thus, we can conclude that analytic hierarchy process is a statistically significant partial mediator of the effect of business intelligence on quality decision making on basis of usage according to employee designation level in the beverage industry in Pakistan.

7. Conclusion

As it’s well known fact that business intelligence speaks to the contraptions and frameworks that assume a key part in the vital arranging process inside an organization. These BI frameworks permit an organization to assemble, store, get to and examine corporate information to help in basic leadership. For the most part these frameworks will delineate business insight in the zones of client profiling, client bolster, statistical surveying, showcase division, item gainfulness, measurable examination, and stock and appropriation investigation that give a boost to organizational competiveness. Research study reveals the impact and usage of BI on the quality decision making from employee and departmental perspective. Case Study analysis has been done on Pepsi Co. to find out significant relationship between BI used in organization on basis of department and employee classification and quality decision making through analytic hierarchy process. Result of regression test signifies the positive association between BI and decision making. The Sobel test is used to find out the mediation level. As P value is less than 0.05.Thus, we can conclude that analytic hierarchy process is a statistically significant partial mediator of the effect of business intelligence on quality decision making on organizational departmental level in beverage industry in Pakistan. Use of BI for quality decision making is very constructive and profitable for beverage industry. As BI has implemented at departmental level and expected to be move forward to corporate for its fullest benefits utilization. It is facilitating to craft decisions (investment, financing, profit distribution and customer retaining etc) through potentiating patterns to understand the business processes.

So well-planned BI applications can give organization the capacity to settle on better choices by rapidly understanding the different "data resources" and how these connect with each other. These advantages can incorporate client databases, store network data, work force information, fabricating, item information, deals and advertising action, and in addition some other wellspring of data basic to your operation. A powerful BI application, which incorporates joining and information purifying capacities, can permit you to coordinate these divergent information sources into a solitary lucid system for constant reporting and nitty gritty investigation by anybody in developed endeavor – clients, accomplices, representatives, supervisors, and administrators.

Analytic Hierarchy Process (AHP)

Strategic Decision Making (SDM) Business Intelligence System (BIS)

Figure 1: AHP as mediator between BIS and SDM

Table 1: Regression IV(BIS) predicting DV(QDM)

Coefficients

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

2.226

.411

5.422

.000

BIS

.380

.137

.270

2.779

.007

Table 2: Regression IV(BIS) predicting MV(AHP)

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

2.586

.271

9.546

.000

BIS

.306

.090

.324

3.391

.001

Table 3: Regression IV(BIS) and MV(AHP) predicting DV(QDM)

Model

Unstandardized

Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

1.280

.556

2.300

.024

BIS

.268

.141

.191

1.901

.050

AHP

.366

.149

.246

2.451

.016

Table 4: Preacher and Leonardelli (2017) Calculation for the Sobel test

Table 5: Regression IV(BIS) predicting DV(QDM)

Model

Unstandardized

Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

1.998

.430

4.644

.000

BIS

.377

.118

.307

3.189

.002

Table 6: Regression IV(BIS) predicting MV(AHP)

Model

Unstandardized

Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

2.158

.271

7.972

.000

BIS

.374

.074

.453

5.026

.000

Table 7: Regression IV and MV predicting DV

Model

Unstandardized

Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

1.316

.544

2.419

.017

BIS

.259

.131

.211

1.982

.050

AHP

.361

.158

.212

1.997

.049

Table 8: Preacher and Leonardelli (2017) Calculation for the Sobel test

References

1. Apte, C. V., Hong, S. J., Natarajan, R., Pednault, E. P. D., Tipu, F. A. and Weiss, S. M. (2003). Data-intensive analytics for predictive modeling. IBM Journal of Research and Development, 47(1), 17-23.

2. Armstrong, R., Gallo, J. and Williams, S. (2013). BI expert’s perspective. Business Intelligence. Business Intelligence Journal, 18(1), 40-45.

3. Bacon, C. J. (1992). The Use of Decision Criteria in Selecting Information Systems/Technology Investments. MIS Quarterly, 16(3), 335-353.

4. Buckhout, S., Frey, E. and Nemec, J. (1999). Making ERP succeed: Turning fear into promise. Journal of Strategy and Business, 15, 60-72.

5. Byun, D. H. (2001). The AHP approach for selecting an automobile purchase model, Information and Management, 38(5), 289-297.

6. Chaudhry, M.S., Iffat, N., and Safdar, M.(2016). Critical Failure Factors and Significance of Business Intelligence System on Decision Making in Pakistan. Journal of Statistics,23,158-173.

7. Chen, H., Chiang, R. H. L. and Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188.

8. Duedahl, M., Andersen, J. and Sein, M.K. (2005). When models cross the border: Adapting IT competencies of business managers. Management of Computing and Information Systems, Agder University College Kristiansand, Norway.

9. Hagel, J. and Brown, J. S. (2001). Your next IT strategy. Harvard Business Review, 79(9), 105-113.

10. Mohammad, H. A. (2012). The Impact of Business Intelligence and Decision support on the Quality of Decision Making. Middle East University, 74-90.

11. Preacher, K. J. and Leonardelli, G. J. (2017). Calculation for the Sobel test: An interactive calculation tool for mediation tests, http://quantpsy.org/sobel/sobel.htm

12. Rajteric, I. H. (2010). Overview of Business Intelligence maturity models. Management, 15(2), 47-67.

44270607763fc32aea52ba8b8b8d76fba944.pdf

The Research Centre of the Faculty of Economics cordially invites you to a research seminar

on Tuesday, 24th January 2017

at 1 p.m. in room P-119

at the Faculty of Economics, University of Ljubljana

Author: prof. dr. Aleš Popovič, Faculty of Economics, University of Ljubljana

will present the article:

“Business Intelligence Capability: The Effect of Top Management and the Mediating Roles of User Participation and Analytical Decision-Making

Orientation”

“The potential of information systems to improve decision making in order to advance firm

performance has largely been highlighted in the information technology (IT) business value

literature (Melville, Kraemer, & Gurbaxani, 2004; Mithas, Ramasubbu, & Sambamurthy, 2011). In

firm performance studies, information systems have been found to support timely decisions,

promote innovation, and offer a means to manage uncertainty central to the business environment

(Dewett & Jones, 2001; Melville et al., 2004). High-quality information, i.e. information that is

relevant, reliable, accurate, and timely (Popovič, Hackney, Coelho, & Jaklič, 2012; Wixom & Todd,

2005) enables enhanced decisions and can, in turn, stimulate improvements in firm performance

(Raghunathan, 1999). To leverage the benefits of high-quality information, firms are increasingly

investing in information systems (Habjan, Andriopoulos, & Gotsi, 2014).

During the last decade, firms have invested significant resources in Business Intelligence (BI)

systems to achieve competitive advantages (Li, Hsieh, & Rai, 2013). BI systems are generally

recognized as complex technological solutions providing quality information from well-designed

data stores, connected with business-friendly tools that give their users timely access to, as well as

the effective analysis and insightful presentation of information, enabling them to make better

decisions or take the right actions (Elbashir, Collier, & Davern, 2008; Li et al., 2013). BI systems

are consistently rated among the top 10 strategic technologies (Gartner, 2016a) as well as the most

important key issues for CIOs (Gartner, 2016b; Luftman & Ben-Zvi, 2010). Despite ongoing

investments in BI and their growing importance, not all firms are equally successful in developing

BI capabilities (Audzeyeva & Hudson, 2015).

Drawing upon the structurational model of technology in an institutional setting we investigate

how top management affects the development of a firm’s business intelligence (BI) capability. We

propose a multiple mediator model in which organizational factors, such as user participation and

analytical decision-making orientation, act as mediating mechanisms that transmit the positive

effects of top management championship to advance a firm’s BI capability. BI capability has two

distinct aspects, namely information capability and BI system capability. Drawing on data collected

from 486 firms from six different countries, we found support for the mediating effects of top

management championship through user participation and analytical decision-making orientation.

These findings contribute to a nuanced understanding of how BI capability can be developed

within firms. This is one of the first studies to comprehensively investigate the antecedents of BI

capability.”

You can register for the free seminar by phone (01) 58-92-490, or via e-mail:

[email protected] by Monday, 23rd January 2017.

You can find all information regarding future research seminars on following link:

http://www.ef.uni-lj.si/raziskovanje/seminarji_in_konference

We look forward to seeing you!

mailto:[email protected]

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The_impact_of_business_intelligence_on_o (1).pdf

Journal of Systems and Information Technology The impact of business intelligence on organization’s effectiveness: an empirical study Md. Shamsul Arefin Md Rakibul Hoque Yukun Bao

Article information: To cite this document: Md. Shamsul Arefin Md Rakibul Hoque Yukun Bao , (2015),"The impact of business intelligence on organization’s effectiveness: an empirical study", Journal of Systems and Information Technology, Vol. 17 Iss 3 pp. 263 - 285 Permanent link to this document: http://dx.doi.org/10.1108/JSIT-09-2014-0067

Downloaded on: 06 August 2015, At: 01:49 (PT) References: this document contains references to 78 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 32 times since 2015*

Users who downloaded this article also downloaded: Ronda Harrison, Angelique Parker, Gabrielle Brosas, Raymond Chiong, Xuemei Tian, (2015),"The role of technology in the management and exploitation of internal business intelligence", Journal of Systems and Information Technology, Vol. 17 Iss 3 pp. 247-262 http://dx.doi.org/10.1108/ JSIT-04-2015-0030 Mohamad Sadegh Sangari, Jafar Razmi, (2015),"Business intelligence competence, agile capabilities, and agile performance in supply chain: An empirical study", The International Journal of Logistics Management, Vol. 26 Iss 2 pp. 356-380 http://dx.doi.org/10.1108/IJLM-01-2013-0012 Janelle Boyton, Peter Ayscough, David Kaveri, Raymond Chiong, (2015),"Suboptimal business intelligence implementations: understanding and addressing the problems", Journal of Systems and Information Technology, Vol. 17 Iss 3 pp. 307-320 http://dx.doi.org/10.1108/JSIT-03-2015-0023

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*Related content and download information correct at time of download.

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The impact of business intelligence on organization’s

effectiveness: an empirical study Md. Shamsul Arefin

School of Management, Huazhong University of Science and Technology, Wuhan, China, and

Md. Rakibul Hoque and Yukun Bao Center for Modern Information Management, School of Management,

Huazhong University of Science and Technology, Wuhan, China

Abstract Purpose – The purpose of this study was to identify the influence of organizational strategy, structure, process and culture on organizational effectiveness and the possible mediating role of business intelligence (BI) systems among them. Design/methodology/approach – Sample data for this study were collected from 225 organizational units in Bangladesh and analyzed using the partial least squares method, a statistical analysis technique based on the structural equation modeling. Findings – The results revealed that organizational factors, such as organizational strategy, structure, process, and culture positively affect both BI systems’ effectiveness and organizational effectiveness. Furthermore, BI systems’ effectiveness partially mediates the impact of organizational strategy, structure, process and culture on organizational effectiveness. Originality/value – BI systems are context-specific and can influence organizational effectiveness. Dearth in research on the influence of organizational factors to BI systems motivates this study to contribute in BI systems literature by proposing a theoretical model and investigating the mediating role of BI systems among various organizational factors and organizational effectiveness.

Keywords Organizational structure, Organizational culture, Organizational effectiveness, Organizational strategy, Business intelligence systems, Organizational process

Paper type Research paper

Introduction In today’s changing business environment, business intelligence (BI) systems play critical role in organizations to support decision-making and improve organizational performance (Ramakrishnan et al., 2012). These systems facilitate firms to store, retrieve and analyze large amounts of information about their operations and allow them to improve strategic and tactical decisions, and gain competitive advantage of the industry (Jones, 2005). Zeng et al. (2007) defined BI as “the process of collection, treatment and diffusion of information that has an objective, and the reduction of uncertainty in the making of all strategic decisions.” It is a set of concepts, processes and methods to improve business decisions, which use information from multiple sources (i.e. internal as well as externally supplied by customers, partners or third parties) to understand business dynamics (Maria, 2005). Elbashir et al. (2008) used the term as business intelligence (BI) to refer to a group of systems for data analysis and reporting, which

The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/1328-7265.htm

Impact of business

intelligence

263

Received 28 September 2014 Revised 15 February 2015

4 April 2015 Accepted 8 April 2015

Journal of Systems and Information Technology

Vol. 17 No. 3, 2015 pp. 263-285

© Emerald Group Publishing Limited 1328-7265

DOI 10.1108/JSIT-09-2014-0067

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http://dx.doi.org/10.1108/JSIT-09-2014-0067

helps top-, middle- and lower-level managers to use relevant and timely information to make better decisions.

Over the past decades, BI has become increasingly important in both the business communities and the academia (Chen et al., 2012). Many researchers found that BI systems yield real business benefits, and it is used by decision-makers throughout the firm for effective decision-making across a broad range of business activities (Chau and Xu, 2012; Ranjan, 2009; Sahay and Ranjan, 2008). It is the input to strategic and tactical decisions at senior management level, and it helps individuals to do their day-to-day jobs at lower management level (Negash, 2004). A recent study suggested that using a BI system is the way of improving business performance by providing actionable information for executive decision-makers to make better decisions (Cui et al., 2007). It has been argued that BI is “both a process and a product”. The process is composed of methods that firms use to develop useful information and intelligence that can help to survive and succeed in the global economy. The product is information that will help firms to predict the behavior of their “customers, suppliers, competitors, products and services, markets, and the general business environment” with a degree of certainty (Wixom and Watson, 2010; Vedder et al., 1999).

Recently, most research in BI emphasized the use of BI in organizations. The IBM Tech Trends Report based on a survey of over 4,000 information technology (IT) professionals from 93 countries and 25 industries, identified BI and business analytics as one of the four major technologies in organizations (IBM, 2011). In an annual survey of IT executives, BI topped the list of the most important applications and technology developments (Luftman and Ben-Zvi, 2010). Businessweek (2011) revealed that 97 per cent of firms with yearly turnover exceeding $100 million were found to use some form of BI. Moreover, McKinsey Global Institute predicted that a 50 to 60 per cent gap between the supply and demand of persons with business analytical skill, as well as a shortfall of 1.5 million data-savvy managers with the know-how to analyze data to make effective decisions by 2018 (Manyika et al., 2011).

In recent years, BI is continued to be a top priority for many firms, and the promises of BI are rapidly attracting many more champions (Evelson et al., 2007). BI systems are broadly adopted or in process to be adopted in organizations today, supporting activities such as managerial decision-making, data analysis and business-performance measurement. Currently, many organizations have been investing billions of dollars to implement BI systems to accomplish the task (Anjariny and Zeki, 2011). BI has permeated various industries including banking, insurance, finance, retail, health care, telecommunications and manufacturing (Olszak and Ziemba, 2006). It has been applied to many areas that are related to the management processes and some of them have formed their own systems with specific characteristics (Li et al., 2008).

However, in practice, ineffectiveness of BI is common in organizations, especially in the context of developing countries. Organizations are facing difficulties in implementing BI. Although BI has been already studied from technological perspectives, some organizations in developing countries still fail to achieve the success with BI applications (Jourdan et al., 2008). This may be because the relationship between organizational factors such as organizational strategy, organizational structure, organizational process, organizational culture and BI systems has remained largely unexamined. It is essential to examine the relationship between organizational factors and BI systems’ effectiveness because the primary objective of BI is to support

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decision-making in organizations. It is also essential to examine the relationship between BI and organizational effectiveness. Therefore, this study attempts to address the following research questions:

RQ1. What is the relationship between organizational factors and BI systems effectiveness?

RQ2. What is the relationship between BI systems and organizational effectiveness?

RQ3. Does a BI system mediate the relationship between organizational factors and organizational effectiveness?

The rest of the paper is organized as follows. Theoretical framework is presented in Section 2. Section 3 explains the research methodology. The research findings are presented in Section 4, followed by discussion in Section 5. Implications are discussed in Section 6, while limitations and future direction are presented in Section 7. Finally, Section 8 concludes the paper.

Theoretical framework The objective of this study is to investigate the impact of BI on organizational effectiveness. In the literature, the related studies suggest that the types of organizational factors in BI applications in an organizational setting are organizational strategy, organizational culture, organizational process and organizational structure. The theoretical model is presented in Figure 1. We will look at the theoretical model for each of the hypotheses in the following subsections.

Organizational Strategy

Organizational Structure

Organizational Process

Organizational Culture

Business Intelligence Systems Effectiveness

Organizational Effectiveness

BI Systems Organizational ImpactOrganizational Factors

Figure 1. Theoretical model

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BI and organizational effectiveness BI is one of the most widely searched terms and remains a topic of interest in both industrial and academic communities (Işık et al., 2013). It is a set of technologies which collect and analyze the data to improve work-flows and organization decision-making (Herschel and Jones, 2005). It is the combination of collecting, cleaning and integrating data from different sources and presenting results that can improve business decisions-making (Akram, 2011). There is a large volume of published studies describing the role of BI on organizational effectiveness. Watson and Wixom (2007) found that BI includes the critical functions that help an organization improve both its performance and adaptation to change. To date, BI applications have focused on managing strategic and tactical business plans and initiatives. Organizations have been using BI to monitor, analyze, report and improve the performance of its business operations. BI helps organization to optimize business performance. It assists corporate managers and decision-makers to make accurate, timely and relevant decision in an organization and, thus, lead to the increases of productivity and profitability of an organization (Olaru, 2014). Turban et al. (2007) revealed that BI improves business organization’s effectiveness. It gives an organization’s suppliers, partners and employees the easy access to the information and the ability to analyze and share the information with others. Based on these arguments, it is hypothesized that:

H1. There is a positive relationship between business intelligence systems and organizational effectiveness.

Organizational factors and BI systems The resourced-based view has been studied mostly to identify the relationship between organizational resources and its impact on value creation (Barney, 1991). A resource-based view explains how organizational resources that are rare, valuable and inimitable, generate sustainable competitive advantages for firms. Organizational resources cover a wide range of valuable assets controlled by the organization, including management skills, organizational strategy, culture, processes, structure, firm attributes, which enables the firm to utilize and ensure enhanced performance (Daft, 1983; Barney, 1991). Researchers have argued for the application of resource-based view of achieving firms’ long-term success by measuring the strategic value of IT resources (Wade and Hulland, 2004). Furthermore, a fit among organizational resources depends on the best possible organizational design that is contingent upon numerous internal and external factors. Based on the contingency theory, previous studies further argued for the importance of fit among subsystems of the organization and the factors such as technology, people, information, strategy, culture, process and structure which ensures ultimate long-term firm performance (Tosi and Slocum, 1984). In other words, the organizational factors are viewed as non-IT resources, subsystems of a firm, and complementary to IT resources (Wiengarten et al., 2013). In line with both resource-based view and contingency approaches, it is proposed that organizational factors, such as organizational strategy, structure, culture and process, impact BI systems’ effectiveness that ultimately affects firm’s effectiveness.

Organizational strategy. BI systems cannot work in isolation; instead, it takes organizational factors to make the organization effective with enhanced performance. The relationship between organizational strategy and BI systems utilization is crucial, thus demands keen attention of top managers. According to Daft (1995, p. 49):

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[…] organizational strategy is a plan for interacting with the competitive environments to achieve organizational goals. Organizational performance largely depends on the sound strategy and its effective implementation.

This study followed Venkatraman’s (1989) strategic orientation of business enterprise (STROBE) framework to analyze organizational strategy. Although the framework elucidates six dimensions to represent organizational strategy, we adopted the revised dimensions examined by Bergeron et al. (2004) where they validated four dimensions such as analysis, defensiveness, futurity and pro-activeness. Analysis refers to the capability of problem-solving through extensive searching with identification of root-causes and best potential results (Miller and Friesen, 1983). By taking conservative measures such as cost reduction and making organization efficient, the defensive behavior can be demonstrated through defensiveness dimension. Futurity dimension defines the simultaneous emphasis on decision-making by considering cost efficiency at present and in the future as well as strength in the long run. Pro-activeness demonstrates to be one step ahead to tap the opportunities such as business diversification with new industries, and continuous searching for market opportunities and exploitation of strengths to become pioneer. Once these four dimensions are incorporated, organizations are more likely to have strategic directions that lead to better performance.

The link between organizational strategy and BI systems’ effectiveness is obvious. One of the major objectives of the BI systems application is to provide useful and timely information, so that top management can make valuable decision guiding organization to achieve success. A core alignment between business strategy and IT strategy is desirable for sound organizational performance. While high-performing firms ensure the strategic IT alignment (Chan et al., 1997), researches reveal that low-performing firms are more likely to face paradoxical position, having poor alignment of business strategy and structure with IT strategy and structure (Bergeron et al., 2004). Although some researchers have argued for strategic IT alignment that depends on the contextual factors such as industry, environmental uncertainty (Kearns and Lederer, 2004; Armstrong and Sambamurthy, 1999), knowledge sharing culture and prior information system (IS) success (Chan et al., 2006); a growing body of researches have demonstrated the role of mediation between organizational strategy focusing on IT capabilities and organizational effectiveness (Bergeron et al., 2001). With this line of argument, we posit that BI systems’ effectiveness mediates the relationship between the organizational strategy and organizational effectiveness. Thus, we propose the following hypotheses:

H2. Organizational strategy (analysis, defensiveness, futurity and proactiveness) will have a positive relationship with BI systems’ effectiveness.

H3. Organizational strategy (analysis, defensiveness, futurity and proactiveness) will have a positive relationship with organizational effectiveness.

H4. BI systems’ effectiveness mediates the relationship between organizational strategy and organizational effectiveness.

Organizational structure. Organizational structure is one of the important organizational factors that constitutes a congenial environment for BI systems’ success. Organizational structure is defined as the pattern of relationships, authority and internal communication among members and tasks (Thompson, 1967). Structure is

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consisted with some common variables such as centralization, formalization, vertical and horizontal differentiation, administrative intensity and professionalization (low complexity). In spite of these scales with different depth and breadth, the common goal of its application is to know the extent to which the administrative decision-making authority is dispersed to hierarchical roles and positions. Although the previous studies varied in measuring organizational structure, most of them emphasized centralization and decentralization as the important features to know how much organization is flexible regarding its tasks and activities. Centralization refers to the degree to which the authority for making a decision is controlled by the organization (Fry and Slocum, 1984). A high degree of authority is expected to execute the decision and implementation, on the other hand, decentralized authority is effective to have organizational innovation (Daft, 1978). A numerous study have suggested that decentralized structure ensures employee’s satisfaction and motivation, flexibility in decision-making, prompt decision and execution, vertical communication, stability in external environmental changes and higher efficiency (Burns and Stalker, 1961; Schminke et al., 2000; Daft, 1978).

Research has found a positive link between decentralized organizational structure and its alignment with firm’s performance and innovation (Evans and Davis, 2005). It is obvious that decentralized structure increases the firm’s performance. In a decentralized structure, effective decisions are taken and implemented promptly at the process level that in turn ensures firm’s performance (Andersen and Segars, 2001). BI systems are seemed to be effective and affect firm’s performance in decentralized structure, by which process-, customer- and suppliers-oriented information is communicated to top authority without any hurdle and delay. Therefore, the following hypotheses can be formulated:

H5. Organizational structure (decentralization) will have a positive relationship with BI systems’ effectiveness.

H6. Organizational structure (decentralization) will have a positive relationship with organizational effectiveness.

H7. BI systems’ effectiveness mediates the relationship between organizational structure and organizational effectiveness.

Organizational process. Organizational process (management process) entails IT, marketing, manufacturing and supply chain management processes. Research reveals that the complementary between marketing and IT, manufacturing and supply chain management processes positively affects firm’s performance (Bharadwaj et al., 2007). Moreover, the integration of these complimentary effects and firm’s IS capability mutually affect firm’s operational performance and enhance organizational effectiveness (Bharadwaj et al., 2007). Similarly, when organizational process (management process) is aligned with IT infrastructure, an organization may experience IT-based capabilities or competencies that lead to enhanced process performance and firm performance (Nevo and Wade, 2010). Furthermore, IT-process alignment builds a strong capability which brings firm’s sustained competitive advantage (Wade and Hulland, 2004; Wiengarten et al., 2013).

When information system is associated and incorporated with organizational processes, a synergistic effect is generally seen that enhances organizational capabilities. For instance, knowledge processes and management processes with

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aligned information systems generate the organizational capabilities that determine organizational effectiveness (Radhakrishnan et al., 2008). Most importantly, BI systems sometimes require to redesign specific organizational processes to adapt to IT infrastructure. An integrated customer and supplier processes help firms to process supplier- and customer-oriented information that increases firms’ capability to exchange information quickly and firm’s financial performance (Barua et al., 2004). BI systems initiate and incorporate the firm’s IT, customer, supplier, manufacturing capabilities to accentuate the operational procedures. The linkage between BI-enabled organizational processes and organizational effectiveness is depended on appropriate utilization of BI systems in the organization. Therefore, we assume that organizational process, consistent with BI systems, impacts firms’ effectiveness through the effective BI systems, and it comes out the hypotheses below:

H8. Organizational process (management process) will have a positive relationship with BI systems’ effectiveness.

H9. Organizational process (management process) will have a positive relationship with enhanced organizational effectiveness.

H10. The association between organizational process (management process) and enhanced organizational effectiveness is mediated by the effectiveness of BI systems.

Organizational culture. Organizational culture is defined as “the pattern of shared values and beliefs that helps individuals understand organizational functioning and thus provides them with the norms for behavior in the organization” (Deshpande and Webster, 1989, p. 4). Schein (1985) emphasized on “shared assumptions” held by employees in an organization. While researchers are not in consensus on which dimension(s) represent(s) organizational culture, we follow the work of Denison and his colleagues (Denison, 1990; Denison and Mishra, 1995; Denison and Neale, 1996; Fey and Denison, 2003) who postulated four dimensions of organizational culture such as adaptability, consistency, involvement and mission. Adaptability refers to the extent to which an organization can cope with the external environment by changing behavior, structures and systems. Consistency is defined as the extent to which an organization has the ability to sustain a shared values, beliefs and norms among organizational employees. Involvement refers to the extent to which an organization allows its members to participate in decision-making. Mission refers to a clear and meaningful explanation of organizational purposes that is shared by all members in an organization.

Organizational culture is empirically related to organizational effectiveness, and conducive and solid organizational culture motivates employees to achieve organizational success. Moreover, organizational culture brings a sustained competitive advantage that is difficult to imitate. Information systems research has identified the positive relationship between firm’s culture and organizational performance. Organizational culture does not impact organizational effectiveness directly, rather it needs people to be influenced and guided to achieve the organizational goals. In the milieu of organizational volatility, both structured and unstructured information lies within and beyond the boundary of the organization and such information exploration would be captured by the employees of organization. In an organization with strong and conducive organizational culture, members’ capability to digest information from

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unknown world is enhanced that leads to make constructive and effective decisions. Organizational culture (involvement, consistency, adaptability and mission) is related to organizational effectiveness such that involvement, consistency, adaptability and mission shape the organization in such a way it is likely to contribute to enhanced organizational effectiveness.

BI systems continuously focus on new information searching by utilizing all channels of data gathering, using information system mechanisms to synthesize and convert the data into useful information, monitoring all operational processes and tracking root-cause of the problems. BI systems’ effectiveness leads to organizational effectiveness, conditioning the antecedent role of organizational culture. Because, shared perceptions, values, norms and beliefs held by organizational members provide a conducive and enduring environment, having free flow of information of suppliers and end customers among organizational hierarchies and different operational departments, such that the organization is benefited through prompt decision implementation, problem minimization and heightening performance. Therefore, the hypotheses are developed as follows:

H11. Organizational culture (involvement, consistency, adaptability and mission) will have a positive relationship with BI systems’ effectiveness.

H12. Organizational culture (involvement, consistency, adaptability and mission) will have a positive relationship with enhanced organizational effectiveness.

H13. BI systems’ effectiveness mediates the relationship between organizational culture and organizational effectiveness.

Research methodology Data collection A quantitative survey was designed and conducted in Bangladesh, one of the emerging countries in South Asia. This study targeted senior managers who took initiative to act out and enforce the BI systems, such as chief executing officers, managers of IT, managers of management information system (MIS), system analysts, human resources (HR) managers and business managers. These professionals were chosen as the respondents because they have vast knowledge of organizational characteristics, BI systems and its impact on firm’s effectiveness.

We compiled a list of firms that had adopted BI systems from a prominent BI software vendor with an agreement of maintaining privacy. These firms have been utilizing technologies to advance business performance for at least 10 years in its respected sectors. A contact list, including mailing, email address and telephone number of each client was collected from the selected vendor. Strategic business units (SBUs) operating under a group of establishment were also emphasized similarly as with the parent organization.

A total of 587 managers in 363 organizations were selected based on the BI software adoption and the length of usage. Multiple respondents were selected from a large organization if the respondents hold managerial positions in IT, MIS and HR departments to reduce the bias. In a small organization, top managers such as chief executing officer and managers of MIS were chosen as information providers of BI systems and organizational factors.

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All items were originally in English. Following the translation-back translation procedure (Brislin, 1980), the items were translated into Bengali. Two bilingual professors who taught MIS at university level in English and Bengali proficiencies were requested to check the translated items. With minor corrections, the revised items were sent to the five selected IT and MIS managers to match their understanding of the items. Some alterations were performed to get the final version of the translated items. Prior to the main survey, we conducted a pilot study of 23 selected managers to ascertain that the questionnaire items fit well to the research objectives. According to the results of this pilot study, the consistency was ensured and revision of the items was done to make sure the conciseness, understandability without redundancy of the items.

A structured questionnaire was prepared for targeted managers. Following the proposition of Dillman (2000), we sent a package including a cover letter, a questionnaire and reply-paid envelope to the recipients through the mail. Along with the mail, an email was sent to each respondent, including a cover letter and a questionnaire to make sure the convenience of giving responses. After four weeks of mailing out, an email was sent to respondents requesting to post back the filled questionnaire. The respondents who failed to respond were given both email and the paper package again after the expiry of another four weeks. Two weeks later, a final request was delivered to remaining recipients who did not respond to the survey. In line with the previous studies (Dillman, 2000; Chatterjee et al., 2002), we found no significant difference between online and paper-based survey.

A total of 302 respondents from 168 organizations sent their responses. Among the respondents, 43 participants responded online. On an average, two managers of a single organization responded. Managers representing a SBU were asked to respond on behalf of either SBUs or their parent organizations.

After checking the responses, 14 questionnaires were found with considerable missing information (50 per cent or more) and, thus, were discarded from the survey. A usable sample of 288 respondents from 154 organizations was finally obtained. Seventy-one respondents provided information on behalf of their SBUs, which was used to match other informants from the same SBU. Sixty-three organizations were holding two or more informants. Therefore, the total sample of organizational unit became 225 by adding SBUs with the list of organizations.

Following the procedure described by Armstrong and Sambamurthy (1999), we averaged the multiple respondents of each organization on the main variables of the sample and conducted the correlation among the responses. We found a high average correlation (0.48; p � 0.05) among the responses provided by respondents of each organization. Thus, the results provided support of the consistency between multiple respondents of each organization. On the other hand, a single informant from an organization was treated as the representative of the organization. Moreover, we found no significant difference between individual and average responses.

The responses represented vast categories of industries in the sample (Table I). The dominant organizations in the sample are from manufacturing industry (54 per cent); this was followed by banking, insurance and financial industries (21 per cent), and then tourism industry (17 per cent). A least sample (8 per cent) is representing retail,

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wholesale and distribution industry. The average size of the firm is large with an average of 558 employees.

The respondents were dominated by males (83 per cent), while females represented very few (17 per cent) with an average age of 43 years old, and the average duration of relevant work experience was 13.4 years. Most respondents (48 per cent) were representing themselves as business executives, while 37 per cent were IT executives, with 15 per cent holding business and IT jobs simultaneously. Fifty-three per cent of the total respondents held experience on BI systems at least five years, while 29 per cent of informants had more than seven years of experience. Therefore, it represents that the informants have a vast experience on BI systems as well as organizational management. We conducted an ANOVA test (p � 0.05) for testing non-response bias. All responses received within the first four weeks were treated as early responses and the rest as late responses. The results show that there are no significant differences between the two samples.

As this study undertook a survey based on self-report on all of the variables, the question of common method bias might arise. In line with the work of Konrad and Linnehan (1995) and Simonin (1997), we conducted Harman’s one-factor test of all variables to measure the possible common method bias in our study. The result of principle component factor analysis revealed six factors with eigenvalues greater than 1.0, while these factors accounted for 70 per cent of the variance. Moreover, the first factor did not account for the majority of the variance (33 per cent). On the basis of these

Table I. Breakdown of respondents

Descriptions Frequency Percentage (%)

Gender Male 187 83 Female 38 17

Age 30-34 16 7 35-39 63 28 40-44 105 47 45-49 34 15 50� 7 3

Industry Manufacturing 122 54 Banking, insurance and financial 46 21 Tourism 39 17 Retail 18 8

Position in organization Business executives 108 48 IT executives 83 37 Both business and IT 34 15

BI systems experience 2-4 years 41 18 5-7years 119 53 More than 7 years 65 29

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findings, we can assume that the common method bias is not a concern in this study (Podsakoff and Organ, 1986).

Measurement items We adopted the existing items used in previous studies for our research. Because of the length of items, we adjusted the items that match with this study. The construct, items and their sources are listed in Table II.

Data analysis. We used structural equation modeling (SEM) to analyze the data and test the hypothesized model. SEM is an important and effective statistical tool that integrates factor analysis (using a measurement model) and path analysis (using a structural model). SEM analyzes all hypothesized relationships simultaneously. Specifically, we conducted a confirmatory factor analysis (CFA) to assess the reliability and validity of the constructs and tested the structural fit of our theoretical model. We applied partial least squares (PLS) in version of Smart PLS 2.0 (Ringle et al., 2005) to analyze the data collected. The following section presents the results of the measurement model estimation and elucidates the hypothesized results of the research model exposed in Figure 1.

Results Measurement model evaluation We tested a measurement model at the item level to check whether scale items were adequate indicators of their underlying constructs. The measurement model revealed six latent constructs (i.e. organizational effectiveness, BI systems’ effectiveness, organizational strategy, organizational structure, organizational process and organizational culture).

The internal consistency statistics were assessed by Cronbach’s alpha and composite reliability (CR) (Dillon Goldstein’s Rho), which were represented in Table III. Both the Cronbach’s alpha and CR of all constructs were above the threshold of 0.7. Therefore, all the items used in this study were found reliable. We proceeded to test the construct validity by measuring average variance extracted (AVE), which measures the percentage of the variance captured by a construct by showing the ratio of the sum of the variance captured by the construct and measurement variance. Table III shows that the AVE of each construct was greater than a threshold of 0.5 (Yoo and Alavi, 2001).

Further, we tested the discriminant validity examining whether a construct better explains the variance of its own indicators than the variance of other constructs. The correlations estimated between every two constructs were from 0.14 to 0.61. Table IV illustrates that the square root of the AVE of each construct, representing in the diagonal positions, was higher than the entries in the corresponding rows and columns. Hence, the results support the discriminant validity of all constructs in the hypothesized model.

Finally, we tested the convergent validity using the factor and cross-loading of all indicator items in relation to their respective latent constructs. In Table V, cross-loadings of all items showed that the measurement items loaded highly on their respective constructs and did not load highly on other constructs. Moreover, the results revealed that all items loaded on their respected constructs with a factor between 0.65 and 0.91. Thus, we can affirm that these measurement items accurately represent distinct latent constructs.

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Table II. Measurement items

Construct Item Source

Organizational effectiveness (5)

OE1: Compared with key competitors, our company is more successful

Lee and Choi (2003)

OE2: Compared with key competitors, our company has a greater market share OE3: Compared with key competitors, our company is growing faster OE4: Compared with key competitors, our company is more profitable OE5: Compared with key competitors, our company is more innovative

BI Systems effectiveness (10)

BI1: BIS improved coordination with business partners/suppliers

Elbashir et al. (2008)

BI2: BIS reduced the cost of transactions with business partners/suppliers BI3: BIS improved responsiveness to/from suppliers BI4: BIS intelligence improved efficiency of internal processes BI5: BIS increased staff productivity BI6: BIS reduced the cost of effective decision-making BI7: BIS reduced operational cost BI8: BIS reduced customer return handling costs BI9: BIS reduced marketing costs BI10: BIS reduced time-to-market products/services

Organizational strategy (12)

OS1: Emphasize effective coordination among different functional areas

Venkatraman (1989)

OS2: Information systems provide support for decision making OS3: Manpower planning and performance appraisal of senior managers OS4: Use of cost control systems for monitoring performance OS5: Use of production management techniques OS6: Emphasis on product quality through the use of quality circles OS7: We emphasize basic research to provide us with future competitive edge OS8: Forecasting key indicators of operations OS9: “What-if” analysis of critical issues OS10: Constantly seeking new opportunities related to the present operations OS11: Constantly on the lookout for businesses that can be acquired OS12: Operations in larger stages of life cycle are strategically eliminated

(continued)

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Structural model assessment. The structural model is examined by incorporating the estimation of the path coefficients and the variance explained R2 values. Specifically, we measured all the relationships of the hypothesized model by describing unmediating and mediating relationships separately. Moreover, bootstrapping (5,000 resamples) generates coefficient and t-statistics.

Unmediated model. Table VI describes the unmediated structural model with the variance explained (R2) and the path coefficients of all the constructs. We found that of BI systems’ effectiveness. Moreover, BI systems’ effectiveness significantly affects

Table II.

Construct Item Source

Organizational structure (5)

ORS1: Any major decision that I don’t require this company’s approval

Ferrell and Skinner (1988)ORS2: In my dealings with this company, no single

matter has to be referred to anyone higher up for a final answer ORS3: My dealings with this company are subject to a lot of rules and procedures stating how various aspects of my job are to be done (R) ORS4: I don’t have to ask company representatives before I do anything in my business ORS5: I can take very little action on my own until this company or its representatives approve it (R)

Organizational process (5)

OP1: Project management rules and procedures formalized via documents such as contract books, sign-off forms, and such

Tatikonda and Montoya- Weiss (2001)

OP2: Formal project management rules and procedures actually followed OP3: Formal progress reviews held (sometimes also called design, gate, phase or stage reviews) OP4: Technology enabled organizational processes to perform well OP5: Strategic planning process actually encourages information sharing and cross-functional cooperation

Organizational culture (8)

OC1: Most people in this company have input into the decisions that affect them

Denison and Mishra (1995)

OC2: Cooperation and collaboration across functional roles is actively encouraged OC3: There is a high level of agreement about the way that we do things in this company OC4: Our approach to doing business is very consistent and predictable OC5: Customers’ comments and recommendations often lead to changes in this organization OC6: This organization is very responsive and changes easily OC7: This company has a long-term purpose and direction OC8: There is a shared vision of what this organization will be like in the future

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organizational effectiveness (� � 0.6180, t-statistic � 7.6298, p � 0.001). Thus, organizational strategy (� � 0.4177; t-statistic � 4.8076; p � 0.01), organizational structure (� � 0.1559; t-statistic � 2.4963; p � 0.01), organizational process (� � 0.2217; t-statistic � 3.0731; p � 0.01) and organizational culture (� � 0.2171; t-statistic � 3.1436; p � 0.01), positively affected organizational effectiveness. Thus, the results support the H3, H6, H9 and H12. The R2 for BI systems’ effectiveness was 0.351, indicating that the variation in the organizational factors explained 35.1 per cent of the total variance the results support the H1. The R2 for organizational effectiveness was 0.486, indicating that the variation in the organizational factors explained 48.6 per cent of the total variance of organizational effectiveness.

Mediated model. Table VII describes the mediated structural model with the variance explained (R2) and the path coefficients of all the constructs. Consistent with the unmediated model, we found that organizational strategy (� � 0.3019, t-statistic � 4.2661, p � 0.01), organizational structure (� � 0.1394; t-statistic � 2.1952; p � 0.01), organizational process (� � 0.2537; t-statistic � 3.6772; p � 0.01) and organizational culture (� � 0.1800; t-statistic � 3.1603; p � 0.01) had a positive and significant impact on BI systems’ effectiveness. Thus, the results support the H2, H5, H8 and H11. It is noteworthy that after controlling BI systems’ effectiveness, organizational strategy (� � 0.3702; t-statistic � 4.2571; p � 0.01), organizational structure (� � 0.1354; t-statistic � 2.1815; p � 0.01), organizational process (� � 0.1422; t-statistic � 2.2164;

Table III. The measurement model

Constructs AVE Composite reliability Cronbach’s alpha

BIS 0.6519 0.9493 0.9406 OE 0.5723 0.8693 0.8120 OC 0.7946 0.9687 0.9631 OP 0.7302 0.9312 0.9078 OS 0.6732 0.9611 0.9559 OST 0.6889 0.9170 0.8876

Notes: AVE � average variance extracted; BIS � business intelligence systems; OE � organizational effectiveness; OC � organizational culture; OP � organizational process; OS � organizational strategy; OST � organizational structure

Table IV. Correlation matrix and square root of the AVE

Constructs BIS OE OC OP OS OST

BIS 0.8074 OE 0.6067 0.7565 OC 0.3492 0.4224 0.8914 OP 0.4296 0.4531 0.2439 0.8545 OS 0.4622 0.5797 0.2884 0.3293 0.8205 OST 0.2775 0.3048 0.1483 0.2507 0.1569 0.8300

Notes: BIS � business intelligence systems; OE � organizational effectiveness; OC � organizational culture; OP � organizational process; OS � organizational strategy; OST � organizational structure. The principal diagonal of the correlation matrix represents the square root of the average variance extracted (AVE) per construct

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Table V. The cross-loading

matrix

Items Constructs BIS OC OE OP OS OST

BIS1 0.8151 0.2857 0.5373 0.3699 0.4400 0.2973 BIS2 0.8246 0.3309 0.4768 0.3192 0.3547 0.2415 BIS3 0.8168 0.3646 0.4479 0.3475 0.2928 0.1594 BIS4 0.7863 0.2732 0.4263 0.3004 0.3416 0.2649 BIS5 0.7981 0.3270 0.4882 0.3719 0.3686 0.2744 BIS6 0.8528 0.2839 0.5689 0.3700 0.4172 0.1984 BIS7 0.7737 0.2391 0.5013 0.3433 0.4002 0.1692 BIS8 0.7960 0.2260 0.4995 0.3715 0.3545 0.2407 BIS9 0.7893 0.2031 0.4514 0.3286 0.3468 0.1782 BIS10 0.8187 0.2844 0.4676 0.3357 0.3777 0.1883 OC1 0.3355 0.8877 0.3617 0.2032 0.2314 0.1664 OC2 0.3188 0.9112 0.3866 0.2041 0.2591 0.0888 OC3 0.2771 0.8832 0.3623 0.1960 0.2223 0.1287 OC4 0.2671 0.8728 0.3594 0.1810 0.2364 0.1417 OC5 0.3198 0.9022 0.3794 0.1843 0.2691 0.1500 OC6 0.3177 0.9061 0.4053 0.2479 0.3011 0.1028 OC7 0.2938 0.8938 0.3735 0.2799 0.2848 0.1547 OC8 0.3445 0.8737 0.3832 0.2391 0.2507 0.1306 OE1 0.4712 0.2963 0.7397 0.3476 0.4289 0.2184 OE2 0.4520 0.3148 0.7715 0.3774 0.4559 0.2551 OE3 0.4661 0.3567 0.7837 0.3372 0.4565 0.2920 OE4 0.5325 0.3422 0.8227 0.3700 0.4805 0.2097 OE5 0.3505 0.2868 0.6552 0.2725 0.3625 0.1808 OP1 0.3899 0.1749 0.3699 0.8545 0.2688 0.1991 OP2 0.3777 0.2289 0.3495 0.8607 0.2470 0.2498 OP3 0.3692 0.2587 0.3764 0.8416 0.2566 0.1727 OP4 0.3817 0.1990 0.4423 0.8718 0.3484 0.2636 OP5 0.3052 0.1778 0.4007 0.8437 0.2866 0.1869 OS1 0.3539 0.2087 0.4690 0.2448 0.7861 0.1442 OS2 0.4354 0.2039 0.4752 0.2479 0.8141 0.1441 OS3 0.3345 0.2030 0.4164 0.2238 0.8264 0.0998 OS4 0.3378 0.2275 0.4741 0.2816 0.8269 0.0919 OS5 0.4002 0.2009 0.4968 0.3020 0.8303 0.1484 OS6 0.3824 0.2820 0.4764 0.2145 0.8230 0.1962 OS7 0.4131 0.2529 0.4970 0.2902 0.8595 0.1589 OS8 0.3138 0.2660 0.4438 0.2278 0.8272 0.1260 OS9 0.4279 0.2605 0.4513 0.3076 0.8142 0.0790 OS10 0.3573 0.1918 0.4823 0.2900 0.8004 0.1790 OS11 0.3658 0.2506 0.4977 0.2916 0.8115 0.0527 OS12 0.3864 0.2899 0.5161 0.3050 0.8250 0.1294 OST1 0.2209 0.1330 0.2899 0.2289 0.1627 0.8143 OST2 0.2149 0.0528 0.2124 0.1845 0.1205 0.8308 OST3 0.2697 0.1405 0.2573 0.1905 0.1126 0.8712 OST4 0.2648 0.1697 0.2878 0.2414 0.1462 0.8612 OST5 0.1480 0.1031 0.2090 0.1965 0.1069 0.7704

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p � 0.01) and organizational culture (� � 0.1714; t-statistic � 2.4125; p � 0.01) still kept their direct impacts on organizational effectiveness. In addition, BI systems’ effectiveness significantly affects organizational effectiveness (� � 0.3920; t-statistic � 4.5927; p � 0.01), which is essential to represent the mediating role with the organizational factors. Thus, the results support the H4, H7, H10 and H13. R2 for organizational effectiveness was 0.50, which is greater than 0.486 found in the unmediated model. The increased value of the variance explained (R2) of the mediated model over unmediated model indicates that the mediated model has a better fit than the original model.

Following the procedure of Baron and Kenny (1986), we further attempted to examine the mediation effect of BI systems’ effectiveness. Table VIII depicts the results of the mediation hypotheses. We used the Sobel test (Sobel, 1982) to identify the significance level of the indirect effects. The outcomes indicated that the test statistic for organizational structure (z � 2.12; p � 0.05), organizational strategy (z � 3.15; p � 0.01), organizational culture (z � 2.49; p � 0.05) and organizational process (z � 2.66; p � 0.01) predicted BI systems’ effectiveness as a significant mediator.

As Figure 2 shows, all organizational factors initially have a significant total effect on organizational effectiveness. When introducing BI systems’ effectiveness as a mediator, all organizational factors still have a significant direct effect on organizational effectiveness. The results suggest that BI systems’ effectiveness partially mediates the influence of all organizational factors on organizational effectiveness.

Discussion Overall, the study provides empirical evidence for the hypotheses proposed in the research. This study found strong positive relationship between BI systems’ effectiveness and organizational effectiveness. This finding is consistent with past

Table VI. The summary of the results of the unmediated model

Effect Coefficient t-statistics Conclusion

Organizational strategy ¡ Organizational effectiveness 0.4177 4.8076 Supported Organizational structure ¡ Organizational effectiveness 0.1559 2.4963 Supported Organizational process ¡ Organizational effectiveness 0.2217 3.0731 Supported Organizational culture ¡ Organizational effectiveness 0.2171 3.1436 Supported BI systems ¡ Organizational effectiveness 0.6180 7.6298 Supported

Table VII. The summary of the results of the mediated model

Effect Coefficient t-statistics Conclusion

Organizational strategy ¡ BI systems 0.3019 4.2661 Supported Organizational strategy ¡ Organizational effectiveness 0.3702 4.2571 Supported Organizational structure ¡ BI systems 0.1394 2.1952 Supported Organizational structure ¡ Organizational effectiveness 0.1354 2.1815 Supported Organizational process ¡ BI systems 0.2537 3.6772 Supported Organizational process ¡ Organizational effectiveness 0.1422 2.2164 Supported Organizational culture ¡ BI systems 0.1800 3.1603 Supported Organizational culture ¡ Organizational effectiveness 0.1714 2.4125 Supported BI systems ¡ Organizational effectiveness 0.3920 4.5927 Supported

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studies which support the facts that organizational effectiveness is influenced by BI systems’ effectiveness (Elbashir et al., 2008). In the unmediated model, we found that organizational factors such as organizational strategy, organizational structure, organizational process and organizational culture have positive effect on organizational effectiveness. Our findings are consistent with the results of previous studies on the relationship between organizational factors and organizational effectiveness (Hansen and Wernerfelt, 1989; Angle and Perry, 1981).

Organizational strategy has a significant impact on organizational effectiveness above and beyond that of organizational context (Zheng et al., 2010). The contingency theories of organization indicate that different types of organizational structures are appropriate for different types of situations. Duncan (1973) found that different organizational structures were related to the decision unit’s effectiveness and organizational effectiveness. The culture can be studied as an important part of the adaptation process of organizations and that specific culture may be useful predictors of performance and effectiveness of the organization (Denison and Mishra, 1995).

Table VIII. Summary of the

results for mediation effect

Organizational factors Path Path

coefficient SE t-test Sobel test Mediation type

Organizational strategy c 0.418 0.087 4.808*** z � 3.15 (p � 0.01) Partial a 0.302 0.071 4.266*** b 0.392 0.086 4.593*** c= 0.370 0.089 4.257***

Organizational structure c 0.156 0.061 2.496** z � 2.12 (p � 0.05) Partial a 0.139 0.063 2.195** b 0.392 0.086 4.593*** c= 0.135 0.064 2.182**

Organizational culture c 0.217 0.072 3.144*** z � 2.49 (p � 0.05) Partial a 0.180 0.057 3.160*** b 0.392 0.086 4.593*** c= 0.171 0.071 2.413**

Organizational process c 0.2217 0.073 3.073*** z � 2.66 (p � 0.01) Partial a 0.254 0.068 3.677*** b 0.392 0.086 4.593*** c= 0.142 0.067 2.216**

Notes: **p � 0.01; ***p � 0.001

Indirect Effect ba

Indirect Effect

Direct Effect

c′

Total Effect

c Organizational Factors

Organizational Factors

Organizational Effectiveness

Organizational Effectiveness

BI Systems’ Effectiveness

Unmediated Model

Mediated Model Figure 2.

The total effect vs direct effect vs indirect effect

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In the mediated model, it was confirmed that BI systems’ effectiveness partially mediates the organizational strategy, organizational structure, organizational process and organizational culture’s influence on organizational effectiveness. This finding suggests that how well BI is managed is largely associated with how well strategy, structure, process and cultural values are translated into values to the organization. It seems that a logical next step in research on strategy, structure, process, culture and effectiveness could proceed to a deeper level by examining the specific mechanism(s) through which organizational factors influence organizational performance. The findings of this study also strengthen the call for attention to creating a strong organizational strategy, decentralized structure, process and organizational culture that are conducive to implement BI systems.

Managerial implications The results of the present study indicate that BI systems are likely to have a positive impact on organizational effectiveness, when there is a close match between BI systems and organizational strategy, structure, culture and process. The influences of these organizational contextual resources ensure better environmental fit, alignment of organizational resources and ultimate firm performance. Although organizational and BI systems’ effectiveness display the deficiencies in operational performance occurred in process level, the problem may lie in the internal environment level, which is crucial for BI systems’ utilization. This study sheds light on the friendly environment of BI systems that is consisted with a perfect match among organizational strategy, structure, culture and process.

While the pervasive role of BI systems has accentuated by increasing operational, supply chain and customer service performance in recent years, the utmost influence of BI systems is to facilitate strategic decision-making. The results indicate that organizational strategy has the highest impact on BI systems’ effectiveness in comparison with the other organizational factors. It is obvious that aligning organizational strategy with BI systems is the most critical to organizational success. The numerous acceptability and utilization of the BI systems also reflect the strategic soundness of the organization that touches every stage of business process beginning from suppliers to satisfying the end customers.

BI systems’ success varies in terms of firm, industry, the size of the firm, while any failure in utilization of BI systems demonstrates that the problem lies in not only the operational level, but also the core level of business such as structure, strategy, culture and process. To achieve successful change initiatives, the concentration should be paid in how organizational factors can be aligned with organizational demands and activities. This alignment meets success when the change initiatives are taken through focusing equal consideration in diagnosing process level and organizational factor-level deficiencies.

The study has found the simultaneous impact of organizational factors on BI systems, such that organizational strategy, structure, culture and process act as interdependent systems that influence organizational effectiveness through BI systems. Any change in one or two factors requires a change in the remaining organizational factors. This finding provides new insights, as we addressed the impact of all components of organizational factors on BI systems, rather than one or two components of organizational factors.

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Limitations and future directions As like with most researches, the outcomes of this study should be interpreted in light of its limitations. First, the sample of this study is drawn from one single vendor of BI software. Although it ensures the internal validity of the measures, the external validity might be affected if multiple BI software vendors were chosen with different software specifications.

Second, a large number of our respondents are the only informants of their organizations. Among 154 organizations, only 63 organizations had multiple respondents. Although responses from single informant as well as managers might overstate or understate the current scenario of the organization, this limitation cannot be overlooked.

Third, the nature of this study is cross-sectional, unless we gathered information on different time frames, we cannot confirm the causality. Further study replicating our hypothesized model with longitudinal data can unfold the causal relationship among variables. Finally, the length of operations in a single industry can give organizations to be matured and benefited from the proper utilization of organizational factors and BI systems as well. Moreover, with the advancement of BI systems and applications of innovative technologies, organizations can ensure the maximum optimization of the usages. With the passage of time, customization of BI software provided by the vendors, may impact organizational effectiveness and competitive advantage over other firms. Future research can replicate the present study on organizations that are using other BI software provided by other BI vendors.

Conclusion The primary objective of this study is to identify the impact of organizational factors on BI systems. Although it is concluded that the effective BI systems brings better organizational performance, it is important to unfold the influence of organizational strategy, structure, culture and process on this relationship. The results reveal that organizational strategy, structure, culture and process are positively related to BI systems’ effectiveness. Furthermore, BI systems’ effectiveness partially mediates the relationship between the organizational factors and organizational effectiveness. This study contributes to the present understanding of the relationship between BI systems and organizational effectiveness by incorporating organizational factors as antecedents, such that appropriate and effective organizational factors act as a catalyst to engender the benefits of BI systems.

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Corresponding author Yukun Bao can be contacted at: [email protected]

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The impact of business intelligence on organization’s effectiveness: an empirical study

Introduction

Theoretical framework

BI and organizational effectiveness

Organizational factors and BI systems

Organizational strategy

Organizational structure

Organizational process

Organizational culture

Research methodology

Data collection

Measurement items

Data analysis

Results

Measurement model evaluation

Structural model assessment

Unmediated model

Mediated model

Discussion

Managerial implications

Limitations and future directions

Conclusion

References

f017d35e3dab73afbb1124c7fc972be978c0.pdf

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

USING INFORMATION SYSTEMS TO STRATEGIC DECISION: AN ANALYSIS OF THE

VALUES ADDED UNDER EXECUTIVE’S PERSPECTIVE

Leticia de Castro Peixoto (1), André Braz Golgher (2) Álvaro Bruno Cyrino (3),

(1) PHD student in Information Science at UFMG, [email protected] (2) Associate professor at Cedeplar/UFMG, [email protected] (3) Adjunct Professor and vice-director at EBAPE/FGV,

[email protected]

Abstract

The impact of the Decision Support Systems (DSS) on the organizational intelligence and structure and on the strategic decisions was examined in the paper. Nowadays there is an increasing demand for investments on Information Technology (IT) due to the higher complexity of this field in the global market. Nevertheless, measurement of that perception, especially for the Brazilian reality, is little known. This study aims to analyze the relation between the use of DSS by executives of highest organization levels and their perceptions of the quality of information delivered, decision making speed, enhancements in organization learning and strategic management, and differences in involvement with subordinates. The theoretical model proposed by Leidner, Elam and Corrales (1995) and Leidner and Elam (1999), the main theoretical foundation of the paper, was adapted to the

Brazilian reality and extended. We conducted a survey with executives of the 1200 biggest companies in Brazil, evaluating the executives’ perceptions. The main results of the paper confirmed past studies and added new dimensions to the benefits provided by the use of information systems, such as the organization learning principles and the strategic planning process. The paper contributes to the theoretical development of information systems and decision-making fields and with organization management, providing knowledge to support the evaluation of the values created by using Information Systems (IS).

Keywords: Decision Support Systems; Executive Information Systems; Business Intelligence; Analysis and Decision Making

1 Introduction

Technology has always aroused feelings that the current existing problems would be solved quicker and more effectively in the near future. In particular, the increasing demand for greater organizational efficiency and competitiveness in the global business requires a structuring of the planning process and decision making in strategic levels, so that it can provide quick and adequate responses to changing markets and competition. Thus, the sustainable competitive advantage in an organization is strongly related to anticipatory and interpretive capacity of the decision maker to develop the formulation and implementation of company strategies.

It has been perceived that intuition, feeling and common sense are not enough to guarantee organizational decision-making efficiency. Exploratory studies show that higher performance firms have more efficient data analysis, which is associated with less reliance on subjective unstructured judgments (Davenport and Harris, 2007; Klatt et al., 2011, Lavalle, 2011). These data-driven decisions guide important developments of Information Systems (IS) initiatives in many industries.

To this end, leaders and managers seek to design and implement Information Systems (IS) and controls that support the decision-making process and ensure more efficient business strategies. Thus, several authors have advocated investments on ISs as an important approach for companies seeking competitive advantage (Brown. 1995; Rackoff and Wiaeman, 1985; Segars and Grover, 1999; Popoviča et al., 2012; Chen, 2012; Öykü Işika, 2013, Sharma, 2014; Peters, 2016). These systems support the process of decision-making at the operational, tactical and strategic levels (Simon, 1997). Researchers have adopted different approaches to assess the contributions of ISs in gaining competitiveness. Rackoff and Wiaeman (1985) present a methodology relating investments on IS to different strategies of cost reduction, differentiation, innovation, growth and strategic alliance. A different approach was proposed by Segars and Grover (1998), who claim that the quantification of ISs benefits cannot be reduced to financial measures, such as return on investments and internal rates of return. The measurement should also incorporate intangibles contributing to the decision- making processes, such as ability to identify problems and new business opportunities, and ability to generate new ideas and to adapt to unexpected changes.

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

Like every other organization initiative, in general, IT implementation also takes time to realize their full potential to create real increments in innovation processes (Roberts, 2016). Any evaluation of IT benefits must recognize this time-lagged aspect and asses benefit over a temporal horizon of analysis (Devaraj, 2002), even mitigating economic inefficiencies in the business dynamics (Sanches and Albertin, 2009). Therefore, it is necessary to specify a rigorous method to measure the business value created by IS implementation. Some frameworks consider the specificity of contexts of IS use by designing performance measurements for these IT- intensive systems (Delone and Mclean, 1992; 2003; Elbashira, 2008; Sanches, 2009).

Marchand et al. (2001) study some capabilities that influence the information use in companies. He believes that the use is more effective if the company can link capabilities: people behavior and values for the decision-making process, information management practices and information technology practices. According to this perspective, Leidner et al. (1995) and Leidner and Elam (1999) linked the use of ISs by executives with gains in decision making speed, improvements in problem identification, and the advancement of analytical capacity of users, characteristics that contribute to the strengthening of cognitive models and learning of executives.

Following the intangible aspects that contributes to IS’ progress, Öykü Işıka (2013) studies the relationship between some specific IS capabilities and its successfulness. The results pointed to an insightful picture of the factors influencing the IS successfulness, showing that some capabilities’ effects were also moderated by the decision environment characteristics of the organization. Similarly, Petter, DeLone, and McLean (2013) identified variables possibly influencing IS successfulness. These variables were: user expectations, extrinsic motivation, organizational role, user involvement, domain expert knowledge, management processes, and organizational competence.

Although results of previous studies demonstrate the benefits of ISs to improve the performance of companies, these systems very often do not meet the needs of individuals who require the information (Crockett, 1992; Watson and Frolick, 1993). The complexity of the systems, the time required by decision-makers for their use and the high cost of implementation often deter the system to provide effective results (Gorry and Morton, 1989). Furthermore, even analyzing more revolutionary IS, recent researches pointed out that there is no evidence that ISs can promote cost reduction (Kwon and Lee, 2014; Hazen and Boone, 2014). Many costly and complex initiatives undertaken to implement these IS technology have experienced high rates of failure (Foshay, 2015; Kwon and Lee, 2014). However, there is no clear presentation of how these failures are measured.

Failure is then defined by the absence of proven success (Schlaefke and Silvi, 2013), rather than more tangible factors. In this sense, the studies of models to access the maturity of the business analysis capacity in organizations (Foshay, 2015) to validate the effectiveness of information management practices (Kettinger and Marchand, 2011), and to relate business analysis to decision making (Schlaefke and Silvi, 2013) have become even more frequent and relevant.

In fact, most people have mixed perceptions of the contribution of IT for the decision-making process (Devaraj, 2002; Petter, 2008; Popoviča et al., 2012; Sharma, 2014), finding decisions on infrastructure investments difficult to implement because they often do not know what they are receiving or what business capabilities will be provided and how it will lower costs or facilitate new business development (Marchand et al., 2000). Analysts believe that efficient decision-making process gathers information differently, depending on their orientation and cognitive style (Lee and Chem, 1997, Rai and Bajwa, 1997; Fetzner and Freitas, 2011). Enhancing the idea that the IT practices themselves do not result in higher organization performance (Marchand, Kettinger and Rollins, 2001), although these many systems that support decision making and information management are applied globally, their benefits are perceived differently, as a consequence of these multiple perspectives, orientations and styles. Therefore, the constant dissociation between the information generated and demanded in the various organizational levels can be explained by the different characteristics of the decisions to be taken and the diversity of individuals responsible for them.

In this sense, the objective of this paper is to present an analysis of the extent to which senior leaders of Brazilian organizations realize that the use of the Systems Decision Support (DSS) contributes to the process of making the involvement of subordinates in decision-making process more effective and to ameliorate the strategic planning and organizational learning processes. To this end, the article is divided in 4 sections, besides this introduction. Next section presents the theoretical foundation and hypotheses of the paper. Third section describes the methodology and the following section presents the results. Finally, last section concludes the paper.

2 Theoretical Background and Hypothesis

The study aims to relate the greater or lesser use of DSS by senior executives with the perceived benefits for the intelligence and organizational structure and strategic decisions in the Brazilian largest firms. Organizational intelligence would be the result of the organization effort to acquire process and interpret internal and external information (Porter, 1980). It refers to the ability of a corporation as a whole to gather information,

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

innovate, create knowledge and act effectively based on the knowledge it has generated. Thus, an organization needs quality information availability that can be used for strengthening and sharing mental models that best enable it to make strategic decisions, directions and planning in order to keep a virtuous learning cycle.

Gains in efficiency of decision-making process in relation to their subordinates, and in strengthening the mental model of managing were reported by Leidner et al. (1995) and Leidner and Elam (1999). A general discussion of the theory presented by these authors concerning the ISs as tools to support strategic decisions and organizational aspects that influence the greater or lesser use of these systems, known as the Leidner theoretical model, is presented in sections below.

2.1 Information systems for policy making

The study aims to relate the greater or lesser use of DSS by senior executives with the perceived benefits for the intelligence and organizational structure and strategic decisions in the Brazilian largest firms. Organizational intelligence would be the result of the organization effort to acquire process and interpret internal and external information (Porter, 1980). It refers to the ability of a corporation as a whole to gather information, innovate, create knowledge and act effectively based on the knowledge it has generated. Thus, an organization needs quality information availability that can be used for strengthening and sharing mental models that best enable it to make strategic decisions, directions and planning in order to keep a virtuous learning cycle.

The term "DSS" first appeared in the text of Gorry and Scott Morton (1989), who built a framework for improving the ISs using Anthony’s category (1965), and activity management, and the taxonomy of types of decisions proposed by Simon (1960). Anthony (1965) developed a model that divides the management activity in three categories: operational control, management control and strategic planning. The crossing of this study with Simon’s view (1960) on structured, semi-structured and unstructured knowledge generates a rich framework of analysis of the extent of ISs interaction in supporting decision-making (Anthony, 1965). Figure 1 (Appendix) shows the result of the contribution.

According to Anthony (1965), decisions occur at three levels in the organization. Understanding them contributes to the adhesion of an IS applied to the process of decision making in an organization. The first level consists of strategic decisions as setting the company positioning in the market, when the objectives and goals, success factors and external threats are scaled from the information pool and processed. The second level, the management control, is the implementation of these decisions, representing a tactical level, involving the use of information technologies for development of activities of collection, analysis and synthesis of

information. And the third, represented by a more operational decision level, involves the integration between the various areas of the organization, requiring more detailed information in order to monitor the firms ‘activities. Notice from the details of figure 1, that these levels are further divided by types of structured, semi- structured and unstructured activities

Besides the three classical levels of company division defined by Anthony (1965), Laudon and Laudon (1996), an additional layer is included between the operational and tactical/management levels called the level of expertise (knowledge level). At this level, there are engineers, lawyers, scientists, analysts, and marketing, finance and controlling officers, whose work is the creation of new information and knowledge, by creating systems of knowledge and information: knowledge work systems (KWS), office automation systems (OAS) and office information systems (ISO). These systems are shown in figure 2 (Appendix).

Laudon and Laudon (1996) call Transactional Processing Systems (TPS) the systems that meet operational needs. The TPSs are linked to transactions and day-to-day support to the company business. Systems are highly structured and are represented by existing Enterprise Resource Planning (ERP).

At the tactical level, in which operational activities are monitored and controlled, there is the Management Information Systems (MIS). The MIS provides summaries of operational transactions carried out in TPSs, allowing managers to monitor their progress and compare their performance against established standards.

At the strategic level, decisions are less structured and related to the positioning of the organization when facing changes in their environment and associated with the planning of the internal consequences of this positioning. Information systems that support managers and directors in this hierarchical level are known as Executive Support Systems (ESS) (Laudon and Laudon, 1996).

Thus, the DSS are classified according to the hierarchical level at which decisions are made (Laudon and Laudon, 2006). The focus of this study is the DSS at the top of the organizational pyramid, that is, the systems for decision support aimed at managers and directors.

2.2 Decision Support Systems (DSS): concept and history

Decision-making is the process of choosing a course of action over another, looking for appropriate solutions for the new problems that arise in a changing world (Cyert, Simon and Trow, 1956; Simon, 1965). Decisions are made in internal and external situations of a particular business with a certain level of experience and

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

skill, in a particular culture or organizational structure and in a particular set of technologies.

Management Information System (MIS), the first system to support management decision, emerged in late 1960’s. MIS was used to generate a limited range of predefined reports, including reports of economic results, balance sheets and sales. However, the role of information support to decision-making was not substantially implemented yet. This system was superseded in 1970 by the information system called the Executive Information System (EIS), which is under the umbrella of the Executive Support System (ESS), and provided assistance for specific tasks of decision- making (Watson, 1991). The EISs were classified by many researchers as DSSs (Van Den Hoven, 1996; Petrini and Pozzebon, 2004; Arnott and Pervan, 2005; 2008; 2012), and are enterprise reporting and analysis systems.

The promise of information support to decision-making, first attempted in information systems management in the 60 and 70’s, have been gradually successful. The big bet was made in the 90s, after the introduction of decentralized computing, the personal computer (PC), with the arrival of new databases. Among them, the Business Intelligence (BI) tool aims to manage relevant information in order to make the decision-making process more efficient and agile for business leaders (Petrini and Pozzebon, 2004; Petters, 2016). The role of information systems in business has been expanding since the 60s and includes more than the strategic support. Some researchers consider that IS covers managerial and strategic decisions, supporting senior professionals under this umbrella (Arnott and Pervan, 2012).

BI is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information (Lönnqvist and Pirttimäki, 2006; Turban, 2009), acquiring, analyzing and disseminating information relevant to business activities. Thus, BI is a comprehensive strategy that supports reporting, analysis and decision making these actions operational and strategic in organizations (Hannula and Pirttimaki, 2003; Sharma, 2011; Popoviča et al., 2012), providing a consolidated review of data and reports in a suitable format that helps users to make wiser decisions. Consequently, it improves the firm competitiveness (Chou and Bindu, 2005), making decision-making more efficient, increasing productivity (Rainer and Watson, 1995; Vries, 2004) and saving costs of distributing information (Bajwa et al., 1998).

The definition of DSS used in this study approaches the concept of Arnott and Pervan (2005) and Leidner et al. (1995). Arnott and Pervan (2005), broadly define DSS as the area of "information systems", which focuses on supporting and improving management decision- making. This definition of DSS, ESS and EIS includes

the Online Analytical Processing (OLAP), Data Warehouse (DW), BI and more lately the Big Data Analytics (BDA), as recent researches has pointed out that the future of the DSS is somehow related to Big Data Analytics. Chen (2012) and Loebbeck and Picot (2015) consider that Big Data Analytics is an evolution of BI, because it amplifies the BI scope. Under that perspective, BI would not only focus on integration and communication of structured and semi-structured data inside enterprise databases. It would also try to retrieve value from treating unstructured data, which constitute 95% of Big Data Analytics applications (Gandomi and Hairder, 2015). Moreover, some researchers identified DSS types that are separated by technology, theoretical foundations, user types, and decision tasks (Arnott and Pervan, 2008; 2012).

The DSS defined by Leidner et al. (1995) is a computer system that includes most, but not necessarily all, of the following: a single database, in which internal financial data and operational and external data can be found; a friendly interface with the end user, with the ability to generate trends; analytical reports highlighting the critical information to executives and the capacity to obtain data from multiple sources.

Even if all these components of the DSS mentioned by Leidner et al. (1995) and Arnott and Pervan (2005) are present in information systems, companies are presented in different stages of evolution, and might not be able to fully implement all of them. In this vein, the literature presents some models that address the maturation process of ISs in organizations (Mcgee and Prusak, 1994; Choo, 2003; Hatcher e Prentice, 2004; Kettinger and Marchand et al., 2011). With the objective of better categorizing the levels of development of DSS in organizations, we used the model of developmental stages of IS proposed by Hatcher and Prentice (2004).

The maturity model proposed by these authors enables an organization to objectively evaluate the use of information resources in five levels: operations, consolidation, integration, optimization and innovation. At the operational level, the company emphasizes the activities required to support the day-to-day operations and the decisions are made in a chaotic information environment, which is internally competitive, with scarce evaluation criteria and lack of consistent performances. At the consolidation level, the company has combined information in a database for functional or departmental decision-making, but there is little information control from the perspective of the organization, as there is no automatic integration and access to data. At the intermediate level, integration, there is recognition of the importance of data and consistent information for the achievement of the firm goals. The result is that information is widely accepted as an essential tool for success and competitive advantage. At the optimization level, the company begins to look for ways to maximize performance to

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meet market demands. They seek to ensure constant alignment of the information system with the market and to quickly optimize the entire business process and value creation. On the last level, innovation, the company starts to realize that it is achieving decreasing returns of its optimization efforts and technology investments. It recognizes the need to leverage their knowledge by introducing innovative and differentiated products and services.

Recently the Kettinger and Marchand’s (2011) model also defines levels or stages of maturity (detection or perception, collection, organization, processing and maintenance) for the use of information in decision- making. However, the stage of greater maturity does not foresee increases in the process of organizational innovation, as in Hatcher and Prentice Model (2004). Davenport and Harris (2007) developed a similar model presenting the following stages or levels of maturity: structure, singularity, research, access and governance.

This study considered that a company had an implemented DSS if it could be classified in the integrated levels of consolidation, integration, optimization or innovation (Hatcher & Prentice, 2004). Only those in the level of operation, which involves activities with very little systematic operational use of information, were not considered in this study. Thus, Brazilian companies were classified according to these categories with the intention to standardize the inferences originating from results.

2.3 The use of DSS and organizational intelligence

Information-oriented companies tend to better understand the value of integrity in the formal use of information (Marchand et al., 2001). Integrity in terms of shared values – honesty, candour, and openness – where people trust the formal information sources inside the company. According to Marchand (2001), the information orientation of a company can be strengthened with the interaction between people’s behavior and values, information management practices and information technology practices. Thus, this information orientation constitutes the key link to business performance, which is related with the ability of taking successful decisions. Based on this model, companies with higher information orientation will excel in business performance.

Leidner et al. (1995) and Leidner and Elam (1999) studied the benefits of the use of DSS and identified the effect of this use in the organization intelligence. The authors proposed that the strengthening of the executive’s mental model increased by the information availability and enhanced analytical power, will promote improvements in the effectiveness of problems identification and choice making. As a result, the use of information systems for decision-making, both

frequency and time in use, would have impacts on organizational intelligence.

More broadly, the impacts on organizational intelligence can be seen through the availability of quality information, strengthening and sharing of mental models and virtuous learning cycles generated in the organization.

2.4 Aspects of the availability of quality information

The intrinsic characteristics of IS influence its use if there is a relationship with level of difficulty in the use of information. A relationship of pleasure or annoyance in searching necessary data for decision-making or a relationship of freedom and constraint in how these relationships are established also influence IS use. Therefore, the characteristics of information systems influence their usability in different perspectives. Although the understanding of this fact is almost intuitive, the measurement of this influence or its direction is problematic (Pozzebon, Freitas and Petrini, 1999). This is because the cause-effect relationships that involve the use of ISs and their resulting benefits perceived may be tied to a very large number of factors, since these may influence the behavior of their users, changing its application in the work place.

Studies on the effectiveness of ISs suggest a positive relationship between perceived quality of information and their use (Auer and Reponen, 1997, Burton, 2001; Chenhall and Moris, 1986; Delone and Mclean, 1992; 2003; Khalil and Elkordy, 2005; Petter , 2008). The quality is also intimately linked with the potential value it can create. Poor data can directly affect negatively in business decisions and thus promote tangible and intangible loss to firms (Hazen and Boone, 2014; Isasi , 2015). The quality is assessed on the following criteria: intrinsic (accuracy and reliability), context (relevance, timeliness, and completeness), representativeness (consistency, ease of interpretation, conciseness) and accessibility (access, security). Moreover, Leidner et al. (1995) and Leidner and Elam (1999) show that users tend to spend more time in ISs that reduce the uncertainty of decisions (Burton, 2001).

2.5 Increases in the process of organizational learning

Increases in the process of organizational learning can create knowledge and act effectively in organizational intelligence. Recent evidence indicates that DSS can enhance executive’s mental models (Leidner et al., 1995; Vandenbosh and Higgins, 1995, Rai and Bajwa, 1997; Elbashira, 2008) And Lead To Faster Decisions (Leidner et al., 1995). It is believed that the effectiveness of management decisions is largely dependent on the quality of their mental models (Van Den Hoven, 1996). Thus, by improving the understanding of executives through better mental models, the use of IS may lead to better responses to problems. Leidner et al. (1995) and Leidner and Elam (1999) reported that increasing the

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

extent of the analysis based on the use of DSS can increase the mental models of executives.

Both individual style and organization idiosyncrasies may be related to different responses regarding the use of information systems for decision-making. Thus, the greater or lesser use of ISs may be a reflection of different approaches of making decisions. What stands out is the ability to learn from the process of decision making, whether individually or organizationally. Therefore, learning has become a new and critical concept in the development of strategies for IS (Senge, 1994; Stein and Vandenbosh, 1996; Audy, 2000; Petters, 2016).

Additionally, the ISs promote greater information and communication flow between organizational units and individuals contributing to the learning process (Balasubramanian, 1995; Argote and Miron-Spektor, 2011). In that way, this process is facilitated by supporting the acquisition of knowledge, distribution and interpretation of information and of organizational memory. There are aspects of organizational learning that benefit from the use of ISs: sharing and distributing information, and better management of knowledge (Balasubramanian, 1995, Stein and Vandenbosh, 1996; Petters, 2016).

2.6 Increases in the strategic planning process

Based on learning principles, it is believed that the availability of multiple information in real time basis and in different forms supplied by the DSS can speed decision making, by the acceleration of problems or opportunities identification (Leidner et al., 1995). However, the perceived improvement in the performance of the decision-making process may increase the time spent in IS searching for more founded analytical decision (Sharda and Barr, 1988; Popoviča et al., 2012). Additionally, it is argued that the easiness of data manipulation can provide more extensive analysis.

Relying on a larger distribution and ability to interpret information acquired by the ISs, the strategic planning process of an organization can be strengthened by greater use of IS. Strategic planning is undertaken in organizations to reduce uncertainty, to coordinate efforts to establish dialogue and communication lines, and to pro-actively seek for business opportunities in a competitive area (Lederer and Burky, 1988; Sharma, 2014). Strategic decisions allow the company to develop and pursue their goals in more effective ways, better considering its relations with the environment in which it operates (Ansoff, 1990). The set of decisions to be conducted determines the behavior in a given time and defines the strategic planning for the period (Simon, 1965). In an organizational decision arena, information is influenced by both external and internal business and by their different organizational levels (Mintzberg, 1976). Therefore, ISs that support the decision-making

process will directly affect the process and the generation of the company strategic planning, contributing to the company development in a constantly changing environment.

2.7 The use of DSS and the organizational structure

The size and heterogeneity of decision-making units and the frequency and duration of meetings vary according to Huber (1991), and technologies that support decisions may affect this. As a result, the centralization of decision-making and the number of organizational levels involved may also be affected by the use of ISs. For that reason, the use of DSS in various decision levels can restructure the organizational structure. In the long term, the DSS can lead to the elimination of staffing levels (Bajwa et al., 1998) and innovation in administrative tasks in the organization (Elbashira, 2008; Roberts, 2016).

Although executives enjoy considerable independence, they rely heavily on their subordinates to report their problems and provide them with recommendations to solve problems (Blankenship and Miles, apud Leidner et al., 1995). According to Leidner et al. (1995) and Leidner and Elam (1999), there are indications that the use of DSSs possibly diminishes the role played by subordinates in these tasks because of greater availability of information outside the realm of the relationship between executives and subordinates.

Because of this, the use of DSS is expected to influence the organizational structure as it changes the process of decision making in the various organizational levels, the dependency on subordinates and, consequently, the information flow throughout the organization.

3 Methodology

We applied a survey as instrument to obtain primary and specific data collection in order to test the hypotheses described in the previous section. With the method, we sought empirical validation of the model proposed by Leidner et al. (1995) and Leidner and Elam (1999). We used the same conceptual framework of these researchers, expanding it when possible. Figure 3 illustrates the research model and its assumptions.

The use of the proposed method aims to address how the organizational intelligence (availability of information, strengthening of the mental model, an increase of the learning process and strategic planning), the organizational decision-making (speed of decision- making and extension of the analysis) and the organizational structure (involvement with subordinates in decisions) correlate with the DSS use. Thus, the question arises about the relationship between the independent, “frequency of use” and “time in use”, and the dependent variables (organizational intelligence, organizational decision-making and organizational structure).

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

In applying the Leidner model to the Brazilian case, the research had a confirmatory nature, since the hypothetical model is pre-specified and the new variables, learning process and strategic planning were not tested, given that they represent extensions of the model. The extension of the model, which added these two new variables, had explanatory nature.

Thus, the study measures the extent to which the use of DSSs influences organizational intelligence, considering the strategic planning and learning, decision making and involvement with subordinates in the largest companies based in Brazil. It is expected that the greater the use of DSS, the more significant these impacts are perceived by executives. Therefore, organizations would, in a sense, be more effective due to the implementation of DSS.

3.1 Variables

Independent Variables

The term "usage frequency" of DSS considers not only the direct use of the system by the executive but also the use of information by the subordinates. The frequency with which this information system is accessed to support the process of decision-making is measured by this variable. It starts from the assumption that the use of ISs depends on the user's belief in the benefits and quality of information provided (Burton, 2001; Giovinazzo, 2009; Popoviča et al. et al., 2012; Öykü Işika , 2013). Even at the individual level, the use of DSS may have organizational consequences and, thus, affects organizational decision-making.

The "time in use" of DSS is related to the period the system is already available for use in the company. We consider the time frame in which the executive is using the system: if the tool is new and has been recently implemented or if it is already known by users and is being improved. Huber (1991) states that when users of advanced information systems reported that the use is leading to higher levels of effectiveness in the fulfillment of organizational objectives, such use tends to increase. As a result, the effects of long-term use are also as important as the frequency of use. Leidner et al. (1995) and Leidner and Elam (1999) emphasize that, over time, executives may develop optimal ways of using the DSS, requiring, consequently, less frequent use than when they started using these tools.

Dependent Variables

The variable of organizational intelligence is related to the use of DSS in many aspects, such as increased awareness of information availability, a more developed mental model and the enlargement of the processes of strategic planning and learning of the organization. The last two variables were not studied by Leidner et al. (1995) and Leidner and Elam (1999) and, as mentioned, represent additions to the model.

The increase of speed in decision-making and the extension of issue analysis are dependent variables that represent the organizational decision-making process by using DSS. The level of use of such systems affects the monitoring and operation of internal and external environments of the organization so that the rapid detection or identification of potential problems can accelerate counter reactions from the company.

The involvement with subordinates is defined by the frequency the analysis and evaluation of business issues are conducted in conjunction with subordinates and the intensity of interactions between executives and subordinates. Traditionally, decision makers rely on subordinates or depend on them for acquiring a better knowledge of problems. Leidner et al. (1995) and Leidner and Elam (1999) state that there are indications in the literature that the use of systems can reduce the role of subordinates in decision-making. Huber (1991) suggests that access to information can change the units of decision if the role of subordinates in decision- making process changes. This could change the decision-making levels of the organization, as believed by Bajwa et al. (1998). In the long run, the ISs can eliminate levels in organizations. The operationalization of the variables exposed in this section is summarized in Table 1, which describes the assumptions of the application of the model illustrated in figure 3 (Appendix).

The higher is the DSS usage frequency by executives

The longer is the time in of DSS by executives

the larger the increments in the learning process

the larger the increments in the learning process

the larger the increments in the planning process

the larger the increments in the planning process

the greater is the perception of information availability

the greater is the perception of information availability

the larger the increments in mental model

the larger the increments in mental model

the faster is the decision making

the faster is the decision making

the greater is the extension of issues analysis

the greater is the extension of issues analysis

the greater is the involvement with subordinates

the greater is the involvement with subordinates

Table I. Hypotheses of the Model. Source: Adapted from Leidner and Elam (1999).

3.2 Sampling procedures and administration of questionnaires

The questionnaire was pre-selected in a similar manner than those used by Leidner et al. (1995) and Leidner and Elam (1999). These authors applied the questionnaires to American, Swedes and Mexicans executives. It was adapted to the Brazilian reality concerning aspects of the strategic planning process and organizational learning.

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The use of structured interviews prior to the application of the survey was important to increase the reliability and adequacy of the instrument. The test of the questionnaire was initially administered to selected executives with similar characteristics than the target population.

After that stage, the actual questionnaire was set in three parts. Instructions for completing the questionnaire and contact phone number were provided in a letter of invitation. The first part of the questionnaire contained the DSS definition. It was important to familiarize the respondent to the research topic and to explain the concept of DSS considered. The second part contained questions regarding the categorization of the respondent and the company, which could identify the profile of the respondent, such as age, education and job issues, and could describe the company in points, such as the level of IT investment as a percentage of revenue and the intensity of competition in the business environment in which the company operated. The last question in this part classified the DSS of the company based on the Hatcher and Prentice model (2004) discussed previously. If the company did not have a formal system of decision support, the respondent was asked to ignore the other questions, which correspond to the third part of the questionnaire. In this third part, there were questions related to the benefits perceived with the use of DSS. Seeking a better apprehension of the characteristics of the phenomena being measured, the second and third parts of the questionnaire were composed mainly by multiple-choice questions or by a Likert scale. The biggest benefit of the Likert scale is to measure graduated degrees of agreement or disagreement to a set of statements (Lakatos and Marconi, 2006).

The universe of this research included the 1,200 largest companies operating in Brazil, taken from the records of Dun & Bradstreet (2006). Executives e-mail addresses were supplemented by a customer relationship database of Fundação Dom Cabral. The universe of larger companies was selected because, potentially, they are more likely to acquire ISs for their management.

The questionnaire was then made available to such companies by e-mail to 1071 executives of this universe. Due to the high turnover of executives, 688 e-mails actually reached the recipient successfully. The administration of the questionnaires was conducted by e-mail and the receiving feedback was accompanied by phone calls. This procedure was also adopted in order to encourage the return of responses. Ninety-seven out of 688 firms that received questionnaires returned them completed, corresponding to the research sample.

The results were analyzed using a series of recognized statistical tools, including testing of hypotheses, parametric and nonparametric significance (Conover, 1999; Norušis, 2003), and multivariate techniques, such

as factor analysis (Hair, 2005), canonical correlation (Mingoti, 2007) and cluster analysis (Hair, 2005).

4 Analysis and Results

Only 97 out of the 688 companies returned the questionnaire. However, because aspects such as the distribution of net revenue, sector of economic activity and geographical region did not show statistically significant differences between the sample and population, indicating that the sample was representative.

Among the respondents, 82% were directors, presidents and vice-presidents and 18% senior managers. 70% were between 40 and 60 years-old, and more than 50% hold a graduate degree. Regarding IT spending within surveyed companies, 49% of the respondents spend approximately 2% of net revenues in IT. This follows Mitra (1996) study, where he found that larger companies spent more on IT as a percentage of their sales than smaller companies.

81% of respondents reported using a DSS. The remaining did not have DSS, but only rudimentary information systems. Out of the 79 respondents who had DSS, 54 completed all the questions in the questionnaire and this is the data used to test the hypotheses of the model. Among these 54 respondents, 61% said they always used the DSS and 30% used frequently, showing that a significant portion of Brazilian organizations implemented systems for management support. Most respondents had DSS for over five years (43%). Another 23% of companies had DSS between four and five years.

This research aims to expand the theoretical model proposed by Leidner et al. (1995) and by Leidner and Elam (1999) adapting it to the Brazilian reality, evaluating the relationship of the use of DSSs with increases in decision-making, intelligence and organizational structure.

4.1 Application of the Leidner model for Brazil

The extraction method used in the model variables was the principal component analysis, and the rotation method applied was the varimax normalization with Kaizer. Thus, as discussed by Mingoti (2007), the fit of the factor analysis model can be judged by KMO criteria and Bartlett's tests, which showed that the data is suitable for factor analysis. Using varimax rotation, as suggested by Mingoti (2005), and using as a means of determining the number of factors the criteria proposed by Hair Jr. (2005a), 5 factors were extracted, each with an Eigenvalue above one. The five factors explained 70% of the total variance.

The factors are presented in table 2. The composition of the factors considered only loads greater than 0.65 to increase the power of the results (Hair, 2005). Cronbach's alpha was used to access the internal reliability of the scale items. All reliability values for the

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variables were above 0.69, which is considered acceptable (Nunally, 1967, apud Leinder and Elam, 1999).

The model variables found for the Brazilian case are very similar to those presented by Leidner et al. (1995) and Leidner and Elam (1999), which shows its high degree of reproducibility. Due to the similarity in the generation of factors, the names given by these authors to the new variables were retained.

N Factor Conbach’s Alfa

Load Factor

1

Mental Model 0.814

L6 Better understanding of the projections

0.745

L7 Best view of the problems / opportunities

0.69

L4 Clearer perception of the process

0.679

2 Information Availability

0.696

L1 Accessibility 0.788 L2 Availability 0.759 L3 Importance of the

Information Content 0.672

3

Extension of analysis 0.719

L8 Increased alternatives decision

0.887

L9 Diversification of sources of information

0.737

4 Decision making speed

0.882

L12 Reduction of the time of decision making

0.887

L11 Speed in decision making

0.861

5 Involvement with subordinates

0.691

L15 Need for assistance in the subject

0.831

L16 Confidence in the subordinate

0.759

Rotation converged in 20 iterations. KMO = 0.724. Test Bartlett's sphericity = 638 with follow p <0.001.

Table 2 - Load factors and reliability test for the Brazilian case.

Following the guidelines of Leidner et al. (1995) and Leidner and Elam (1999), the mean values of the variables related to each factor were estimated, and they were the dependent variable of the model. The normality of the five variables of the model presented was tested and no data require correction, as occurred with Leidner et al. (1995) and Leidner and Elam (1999).

Although all these factors are perceived benefits for Brazilian executives of the existence of DSS, its relation

to the use is still unknown, as discussed in the hypotheses. In order to establish this association, the canonical correlation was applied between the independent variables of use and the five dependent variables. The validation of the results was performed by two criteria: level of significance of the role and magnitude of the correlation. Pillar’s, Hotelling’s, Wilks’ and Roy’s significance level tests were applied, indicating that the correlation model is appropriate.

As shown in table 3 (Appendix), the result of canonical correlation shows that the increase in the frequency of use is correlated with increased perception of information availability, enhanced mental models and the speed of strategic decision making, since the obtained positive coefficients were significant. However, the result of canonical correlation for the variable time in use of ISs does not show significance to any variable of the model. Figure 4 summarizes these results of the Model when applied in Brazil.

4.2 Expansion of the Leidner model for Brazil

Factor analysis was first applied separately for the theoretical variables that were not included in Leidner et al. (1995) and/or in Leidner and Elam (1999) to test two new possibilities of theoretical dimensions. The KMO test and Bartlett test showed that the data was suitable for factor analysis. Thus, using the same procedure of factor analysis described above, we obtained two factors. Cronbach's alpha was above 0.7, which shows high internal reliability of the scale. Table 4 shows that the factors detected confirm the dimensions theoretically constructed with eight variables with loads greater than 0.65.

The composition of each of these factors increased the theoretical dimensions of the DSS influence in the decision-making process because it grouped the factors as expected. Thus, the nominations given to the new dimensions could be maintained: increases in the strategic planning process and in the learning process.

Finally, the 12 variables with factor loading greater than 0.65 in the analysis presented in table 2 in Appendix and the eight additional variables of table 4, which also showed load values greater than 0.65, were evaluated together. The result of factor analysis appears in table 5.

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

Factor Conbach’s Alfa

Fatorial load

1 Increase in the strategic planning process

0.831

Reduction of unexpected situations

0.809

Reduction of potential problems

0.802

Identification of non- predicted problems

0.753

Perceptions of factors affecting outcome

0.727

Implementation planning

0.675

2 Increase in the learning process

0.791

Increased collaboration 0.826 Increased commitment 0.808 Support to the

development of individual competences

0.808

Rotation converged in 9 iterations. KMO = 0.724. Test Bartlett's sphericity = 638 with .p < = 0.001.

Table 4 - Load factors and reliability test for the variables added.

The criteria for fitting the model, as previously stated, were again satisfactory, even though the number of variables was above the recommended, because as suggested by King (1997) and Hair Jr. et al. (1990), the number of observations must be at least five times the number of variables. Thus, this analysis should be done with at least 100 observations. However, according to the authors, this technique can be used in smaller samples, provided that the sample has no less than 50 observations.

The analysis of table 5 points out that the factor previously called mental model was incorporated in two new factors, the increments in the learning process and increases in the strategic planning process. These two components not directly addressed in Leidner et al. (1995) and in Leidner and Elam model (1999) could explain 47% of total data variability. Thus, we defined a new set of factors that measure the benefits perceived by Brazilian executives using DSS. The factors availability of information, extension of analysis and speed of decision-making remained, as the model suggested by Leidner et al. (1995) and Leidner and Elam (1999).

Factor Conbach’s Alfa

Fatorial load

1 Increase in Learning Process

0.8

L9 Increased source of information

0.806

Y27 Increased commitment 0.784

Y28 Support to the development of individual competences

0.727

Y24 Increased collaboration 0.651

2 Increase in the Strategic Planning process

0.775

Y18 Implementation Planning 0.784

Y19 Identification of non-predicted problems 0.755

Y21 Perceptions of factors affecting outcome 0.712

Y20 Reduction of unexpected situations 0.673

3 Speed of Decision Making

0.882

L12 Reduction of time making the decision 0.892

L11 Speed in decision making 0.843

4 Information Availability 0.694

L2 Availability 0.745

L3 Importance of Information Content 0.726

5 Involvement with subordinates

0.688

L15 Need for assistance in the subject 0.858

L16 Confidence in the subordinate 0.696

6 Extension of analysis 0.78

8 Increase in alternatives decisions 0.78

Rotation converged in 3 iterations. KMO = 0.727. Test Bartlett's sphericity = 204 with p < = 0.001

Table 5 - Rotated factor matrix of model variables

The canonical correlation analysis was applied in conjunction, having these six factors as dependent variables and the same two variables, frequency and time of use of DSS, as explanatory. The goal is to determine which of the six dependent variables were significantly correlated with the use of DSSs. However, Pillar’s, Hotelling’s, Wilks’ and Roy’s level of significance found for the model was below the value considered satisfactory, indicating that the data was inadequate. Because of that, one of the variables of the model, the time in use of DSS, which was not significant

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in the previous analysis, was not considered in the application of the technique in this last study. Additionally, dropping this variable from the model reduced the number of variables, benefiting the ratio number of variables versus the sample size, as recommended.

The results for this analysis considering only the independent variable named frequency of use, showed acceptable level of significance for the tests described above. As shown in table 6 in Appendix, the results of canonical correlation show that the increase in frequency of use is positively correlated with increased perception of the learning process and strategic management, information availability and the extension of analysis. Figure 5 summarizes these figures (Appendix).

5 Conclusion

The results of the model proposed by Leidner et al. (1995) and Leidner and Elam (1999) applied to Brazilian companies suggest that only the frequency of use is positively associated with the mental model, the availability of information and the extension of analysis. The strengthening of the mental model accounted for 40% of total variance explained by the five factors. This may indicate that Brazilian leaders realize that a better understanding of problems can influence their mental models. The availability of information, also considered important, explained 15% of total data variance. The other three factors, extension of analysis, speed of decision-making and involvement with the subordinates, together explained less than 9% of the total variance. The variable named involvement with the subordinates had the smallest power to explain total variance, as found by Leidner et al. (1995) and Leidner and Elam (1999).

The findings of this research and those of Leidner et al. (1995) and Leidner and Elam (1999) are compared in Table 7, contrasting the Brazilian scenario to the Swedish, American and Mexican scenarios. The positive correlations are represented by “YES” and the hypotheses with correlation without statistical significance are expressed by “NO”.

We observed many difference between Brazil and the other countries, with greater similarity between Brazil and Mexico. The organizational behavior includes decision and communication styles and cultural issues, implicating in different perceptions of the benefits DSS use. Additionally, some of the criteria for perceived quality of information such as availability, reliability and relevance of content can be more or less relevant according to environmental uncertainty and organizational characteristics of the company (Bajwa et al., 1998; Weill and Oslon, 1989; Elbashira et al., 2008). The time in variable used in Brazil, as well as in Mexico,

showed no significant association with the measured benefits.

The higher is the DSS usage frequency by

executives

BR USA SWE MEX

the greater is the perception of information availability

YES YES NO YES

the larger the increments in mental models

YES YES YES NO

the greater is the extension of issues analysis

YES YES YES YES

the faster is the decision making

NO YES NO YES

the greater is the involvement with subordinates

NO YES YES NO

The longer is the time in use of DSS by executives

BR USA SWE MEX

the greater is the perception of information availability

NO NO YES NO

the largest the increments in mental models

NO YES YES NO

the greater is the extension of issues analysis

NO YES NO NO

the faster is the decision making

NO YES NO NO

the greater is the involvement with subordinates

NO NO YES NO

Table 7 - Comparison of results with the model proposed by Leidner in different countries.

Source: Adapted from Leidner and Elam (1999).

In the extension of the Leidner model proposed here and summarized below in table 8, the significant relationship found between frequency DSS use and the learning process may have been influenced by the increased importance of teamwork. The cultural aspect of collectivism, characteristic of Brazil, could also contribute to this finding. The association between frequency of use and the increase in the strategic planning process can be related to the need to anticipate future scenarios. The positive correlations with these two variables (organizational learning and strategic planning) were considered the most important by executives, as they account for 47% of the total variance among the six factors. It is believed that the strengthening of the mental model is directly related to the learning process (Senge, 1994), which may explain why the mental model variables have become less relevant when we include the new variables in the model. Thus, hypotheses empirically verified were: the larger the increments in the learning process, the greater is the perception of information availability and greater the extension of analysis. Conversely, for the hypotheses

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

associated with time in use variable we did not observe any significant result.

The higher is the DSS usage frequency by executives

Results for Extended Model

the larger is the increase in learning process

YES

the larger is the increments in the Strategic Planning process

YES

the faster is the Decision Making NO the greater is the perception of information availability

YES

the greater is the involvement with subordinates

NO

the greater is the extension of issues analysis

YES

The longer is the time of DSS by executives

Results for Extended Model

the larger is the increase in learning process

NO

the larger are the increments in the Strategic Planning process

NO

the faster is the Decision Making NO the greater is the perception of information availability

NO

the greater is the involvement with subordinates

NO

the greater is the extension of issues analysis

NO

Table 8: Results with the extended model applied for Brazil. Source: Adapted from Leidner and Elam (1999).

The use of systems for decision support has also been related to cognitive styles of managers. The cognitive style can be seen as a set of consistent and differentiated strategies that progress gradually to the processing of specialized information and learning environments (Vries, 2004). Although many tools to support information management are globally applied, the derived benefits from the use of DSS can be differently perceived. Cultural differences or cognitive skills that may influence these perceptions have not been considered in this study; however, it is a venue for future research.

Notes (1) The acronym ERP - Enterprise Resource Planning - is the

information system established by the evolution of MRP - Material Requirements Planning, now the MRPII - Manufacturing Resources Planning and arrived on Enterprise Resource Planning - ERP (Stair and Reynolds, 2002).

(2) “Mental models are considerations deeply rooted, widespread, or even pictures and images that influence the understanding we have of the world and how we act” (Senge, 1994, p. 8).

(3) “Cognitive style refers to the process behavior that individuals exhibit in the development or acquisition, analysis or interpretation of information or the expected value of data for decision making" (Huber, 1983, p.567)

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Copyright: © 2017. Peixoto (et al.) This is an open- access article distributed under the terms of the Creative Commons CC Attribution-ShareAlike (CC BY-SA), which permits use, distribution, and reproduction in any medium, under the identical terms, and provided the original author and source are credited.

Received: 2016-05-10. Accepted: 2017-03-09

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

Appendix

Figure 1

Figure 1. Information Systems diagram

Source: Gorry and Scott Morton (1989).

Figure 2

Figure 2. IS distribution throughout the hierarchy levels of the company.

Source: Adapted from Laudon and Laudon (1996).

Operational Management Strategic

Structured

Semi- structured

Unstructured

Cost / benefit projections Increased production capacity, plant location

Production scheduling

Cash Management

Activity Management

Cost analysis

Budgeting

Sales and production

Merger and acquisitions

New product planning

Research and development

Inventory control, accounts payable

ORGANIZATION HIERARCHY LEVELS

Knowledge

Functional area

Operational

Tactical

Strategic

DSS focus levels of this research

TPS

OAS/ISO

MIS

DSS/ESS

KWS

Sa les

M ar

ke tin

g

Pr od

uc tio

n

Fi na

nc e

Ac co

un tin

g

Hu m

an re

so ur

ce

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

Appendix

Figure 3

Figure 3. Research hypotheses

Source: Adapted by the authors, from Leidner and Elam (1999)

Figure 4

Figure 4. Results of the Model applied for Brazil

Source: Adapted by the authors, from Leidner and Elam (1990)

Organizational Intelligence

DSS use

Information Availability

Learning Process *

Executive Support Systems

- DSS -

Strategic Planning *

Extension of analysis

Strategic Decision Making

Speed

Organizational Decision Making

Involvement with subordinates

Organizational Structure * Variables added to the Leidner Model.

Mental Model

Organizational Intelligence

Mental Model Enhancement

Information Availability

Extension of analysis

Strategic Decision-Making Speed

Organizational Decision-Making

Involvement with subordinates

Organizational Structure

(+)

(+)

(+)

DSS use

Executive Support Systems

- DSS -

Usage frequency

Usage frequency

Time in use

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

Appendix

Figure 5

Figure 5. Results of the model expanded in Brazil

Source: Adapted by the authors, from Leidner and Elam (1999)

Organizational Intelligence

Information Availability

Extension of analysis

Strategic Decision Making Speed

Organizational Decision Making

Involvement with subordinates

Organizational Structure

(+)

(+)

(+)

DSS use

Executive Support Systems

- DSS -

Usage frequency

Learning Process

Strategic Management

(+)

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Peixoto, Leticia de Castro; Golgher, André Braz; Cyrino, Álvaro Bruno. Using Information Systems to strategic decision: an analysis of the values added under executive’s perspective // Brazilian Journal of Information Studies: Research Trends. 11:1 (2017) p.54-71 ISSN 1981-1640.

Appendix

Table 3

N Factor Beta Std.Err. t-Value Sig. of t 1 Mental Model x1 - Usage frequency 0.373 0.107 2.829 0.007 x2 - Time in use (years) -0.104 0.073 -0.789 0.434

2 Information Availability

x1 - Usage frequency 0.446 0.093 3.493 0.001 x2 - Time in use (years) 0.125 0.064 0.981 0.331

3 Extension of analysis

x1 - Usage frequency 0.302 0.141 2.207 0.032 x2 - Time in use (years) 0.006 0.097 0.042 0.967

4 Decision Making Speed

x1 - Usage frequency 0.223 0.123 1.592 0.118 x2 - Time in use (years) 0.026 0.084 0.188 0.852

5 Involvement with subordinates

x1 - Usage frequency 0.005 0.17 0.035 0.973 x2 - Time in use (years) -0.080 0.116 -0.563 0.576

In italics are the correlations with statistical significance.

Table 3. Canonical correlation of the factors for the Brazilian case

Table 6

In italics are the correlations with statistical significance.

Table 6. Canonical correlation of the factors for the Brazilian case, when extending Leidner Model

N Factor Beta Std.Err t-Value Sig. of t 1 Increase in Learning Process

X1-Usage frequency 0,290 0,121 2,145 0,037 2 Increase in the Strategic Planning process

x1 - Usage frequency 0,395 0,118 3,038 0,004 3 Speed of Decision Making

x1 - Usage frequency 0,212 0,122 1,536 0,131 4 Information Availability

x1 - Usage frequency 0,330 0,097 2,475 0,017 5 Involvement with subordinates

x1-Usage frequency 0,030 0,167 0,212 0,833 6 Extension of analysis

x1 - Usage frequency 0,257 0,134 1,878 0,066

implementation-of-business-intelligence-to-increase-the-effectiveness-of-decision-making-process-of-managers-in-companies-providing-payment-services.pdf

Journal of Internet Banking and Commerce

An open access Internet journal (http://www.icommercecentral.com)

Journal of Internet Banking and Commerce, May 2017, vol. 22, no. S8

Special Issue: Mobile banking: A service provider perspective Edited By: Mihail N. Dudin

IMPLEMENTATION OF BUSINESS INTELLIGENCE TO INCREASE THE EFFECTIVENESS OF DECISION

MAKING PROCESS OF MANAGERS IN COMPANIES PROVIDING PAYMENT SERVICES

MOJTABA ZAMANI

Master of Engineering in IT, ecommerce, Yadegar-e-Imam Khomeini

(RAH), Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran

Tel: +989126167505;

Email: [email protected]

MEHRDAD MAEEN

Department of Computer Engineering, Yadegar-e-Imam Khomeini (RAH)

Shahre Rey Branch, Islamic Azad University, Tehran, Iran

MAJID HAGHPARAST

Department of Computer Engineering, Yadegar-e-Imam Khomeini (RAH)

Shahre Rey Branch, Islamic Azad University, Tehran, Iran

Abstract

The most important purpose of this research is implementation of business intelligence to increase the effectiveness of decision-making process of managers in service providing companies (Case Study: Saman Kish Electronic Payment Company). The

mailto:[email protected]

JIBC May 2017, Vol. 22, No.S8 - 2 -

importance and necessity of such research becomes clear according to criteria such as Development of knowledge about techniques to facilitate decision-making in business intelligence, strategic level of business intelligence, tactical level of business intelligence, operational level of business intelligence and quality of business intelligence implementation and absence of a system to provide advice for manager to for decision-making on matters related to business intelligence implementation. In the end, the sample size for this research consists of 30 available experts willing to cooperate who were selected using a combination of Purposive non-probability (judgment) sampling and snowball sampling. Data were collected using first set of measuring tools (tools to measure the effect of variables in order to increase the effectiveness of decision-making process of managers) and the second set of measuring tools (tools to validate “support system for decision making based on the principle of business intelligence implementation in order to increase the effectiveness of decision-making process of managers”). This fact that analyzing "business intelligence techniques to facilitate decision making" can make decision-making process of managers in Saman Kish Electronic Payment Company comprehensively effective is among the most important results of this study. In the end, it was determined that the final difference between the outputs of support system for decision making in this research which are BI+FDSS and average expert opinions has not been significant and has been calculated to be 0.06475 which means there is no significant relation between expert opinions and outputs of " BI+FDSS System". ”Techniques to facilitate decision- making in business intelligence”, ”strategic level of business intelligence”, ”tactical level of business intelligence”, ”operational level of business intelligence” and quality of business intelligence implementation” and “Companies providing payment services”. Keywords: Chines To Facilitate Decision-Making In Business Intelligence; Strategic Level Of Business Intelligence; Tactical Level Of Business Intelligence; Operational Level Of Business Intelligence; Quality Of Business Intelligence Implementation; Companies Providing Payment Services © Mehrdad Maeen, 2017

INTRODUCTION

Development of decision making in an organization is usually in this way that the lowest level of business activity in an organization is the operational level which is repeatedly executed in high numbers in low ranks of the organization and deals with a small amount of data. Decisions at these levels are often in the field of structured issued and are made by low ranked managers. The results of these decisions have short-term and micro effect on the organization. Customers, competitors, business partners, economic environment and internal employees are among factors affecting organizational business intelligence [1]. Technical level in the organization is related to operation which is performed in in the area of middle managers. This operation can include operation at low level, how it is done, reporting and ultimately summarizing useful data for organization's medium-term decisions. Decisions made at this level are often semi- structured and made by middle managers and finally the highest strategic level is related to organization's macro decisions which are made by top managers. Such uses

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are in low frequency and long periods but can be associated with high volume of data and process Decisions at these levels are often unstructured issues and are made by senior managers and the results have macro and long-term effect on organization's direction. The usage of Business Intelligence at strategic level can be considered as a way to help increase overall efficiency and optimize processes together. Such systems focus on some key financial features and other parameters important in increasing the efficiency of the organization. It is obvious that system must also consider external processes of organization in such levels [2]. Different properties of applications in different levels of organization lead to differences in tools, techniques and infrastructures needed for each one. Use of analytical and intelligent tools is done more at higher levels which require high computing with availability of a host of strategic and technical information more than operational information. Operational sector of business intelligence has the responsibility of collecting information and storing them in private data bases [3,4]. Business Intelligence has been raised in enterprise architecture as a new approach which helps managers for making accurate and intelligent decision for bossiness in the shortest possible based on speed in data analysis. Business Intelligence is a framework of processes, tools and technologies which required for transforming data into information and information into knowledge using which managers are able to make better decisions and thus, improve the performance of their organization. Business intelligence is the collection of capabilities, technologies, tools and strategies which helps managers to have a better understanding about business conditions. Business intelligence tools provide visions of past, present and future for individuals. The gap between middle managers and senior managers will vanish by implementation of business intelligence solutions and information required by managers at every level, will be provided at the moment with high quality. Also, the experts and analysts can use simple facilities to improve their activities and achieve better results in an era where time is key in business, companies have resorted to the use of information tools so that they can quickly extract the intended resources. Business intelligence provides great facilities in decision making at different organizational levels, particularly senior managers using analysis and methods of inquiry [5,6]. In fact, since a set of applications and data related to topics of business intelligence in organizations which are designed for helping in analysis and decision making and the fact that these systems have a database of existing knowledge on the subject and a language which is used to formulate the issues and questions and are a modeling program to test the possible decisions, the issues in this research are exhaustion of business intelligence decision makers in organizations due to combination of different methods of deploying business intelligence in organizations, business intelligence techniques to facilitate decision-making, strategic level of business intelligence, tactical level of business intelligence, operational level of business intelligence and implementing quality of business intelligence and also the need to use supporting system for business intelligence decision making in organizations using fuzzy logic to increase trust and confidence in decision-making as well as the need for multiple specialties by using several experts in different fields to solve the problem of business intelligence in organizations. In fact, the supporting system for decision making based on principle of business intelligence implementation will be provided in the present research for the first time in the research field related to the topic to increase the

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effectiveness of the decision-making process in Saman Kish Electronic Payment Company using fuzzy logic entitled BI+FDSS.

THEORETICAL FOUNDATION The term of "business intelligence" has been used for the first time in 1865 by Richard Millar Dunes in Encyclopedia of commercial terms. Organizational Intelligence helps all companies obtain effective and reliable performance without additional hassle and high operating costs and try and error using reporting and data analysis [7,8]. ERP and CRM and other systems and software are critical factors for managing organizations and companies. The mere existence of all these techniques across the organization regardless of organizational culture and systemic approach between employees cannot prove business intelligence in that organization. That is why the words deployment and implementation are used for business intelligence and not the installation because factors other than software packages affect creation of business intelligence, so it is defined as the modern architectural approach, because intelligence is a tangible behavior from the beginning of the process of data compilation until storage and retrieval processes and extraction of required knowledge [9]. Intelligent strategies of a business determine the future direction of organization to achieve long-term goals. Researches show that the main concern of business intelligence for an information technology based organization is solving them. A typical organization with the ability to make decisions quickly with high quality may fail but if the same organization uses business intelligence, not only it can speed up the decision-making process, it can also guarantee decision-making with high quality and fertility [10]. The necessity of deploying business intelligence in organizations in the age of knowledge and in information society can be studied from different aspects. From the perspective of senior management, use of business intelligence tools seems necessary for analyze the current state of organization, setting short-term long-term goals and controlling performance indicators. From the perspective of executive management, this seems necessary for making decision about areas of uncertainty and ambiguity and prediction and estimation of the results of decisions. From the perspective of supply chain management, this seems necessary for controlling and improving relations with suppliers and partners of organization. From the perspective of customer relationship management, this seems necessary for identification, categorization, policy-making and improving communication with customers of organization and so on [11]. Here, we will define the main concepts of research: Business Intelligence Business Intelligence includes a wide range of business processes, applications and technologies using which intelligence data are collected, stored and analyzed and the obtained results are provided for the user in proper way. These users are in fact the decision makers for organization who can make better decisions for organization using obtained results [2]. Managers Decision Making Decision-making is an integral part of management process in each organization and at

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all organizational levels. Weber has considered decision making as "determined task of managers". Since some managers enjoy success in decision-making more than others, many studies have been carried out for evaluation of roots, causes and elements which are effective in decision making process. Rove and Bolgharidz state that the best way to get to know the managers in studying their decision-making methods [12]. Based on concluded studies and theoretical literature review and research background, the following Table 1 shows the theoretical framework of research for evaluation of implementation of business intelligence in order to increase the effectiveness of the decision-making process of managers in service providing companies (CASE STUDY: Saman Kish Electronic Payment Company): Table 1: The theoretical framework.

Levels of business intelligence Implementation of business intelligence

Viviers et al. [13] and Ansari et al. [8] and Hosseini et al. [14]

Haghighat et al. [3] and Safarzadeh et al. [4] and Maté et al. [1] and Kao, et al. [2]

A) Strategic level

 Increase organizational performance and optimize processes

 Focus on financial characteristics, other important factors in the increased focus on businesses

 Focusing on external processes

A) Strategic planning

 Various types of modeling in the development of the organization,

 Information about the realization of the strategy, Mission and objectives and tasks of the organization,

 Identify problems and bottlenecks,

 Provide information on the institutional environment and market trends.

B) Technical level

 Follow-up activities

 Medium-term decisions

 Provide periodic reports of the process

 Image provided an overview of the organization's activities for managers

B) Improve relationships with customers:

 Providing sales representatives with appropriate knowledge and sufficient to meet the needs of customers

 Providing a level of customer satisfaction each other with the productivity of business practices and identify market trends.

 Analysis of productivity products and services apparent, among other things

C) The operational level

 Monitoring of business activities

 Preparing of business processes

 Making short-term decisions in carrying out business activities

 Focus on conducting internal business processes

C) The analysis of the operational efficiency of the organization

 Provide analysis of deviations from the realization of projects Providing knowledge and experience to develop and launch new products on the market

 The exchange of knowledge among research teams and sections of the

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company.

 The operational efficiency of internal processes

D) The control and management accounting

 The analysis of the real costs

 Analysis of financial flows

 The organization is committed strategic level

 Increase organizational performance and optimize processes Focus on financial characteristics,

 Other important factors in the increased focus on businesses Focusing on external processes

Techniques to facilitate decision-making in business intelligence Muntean et al. [15], Wieder and Ossimitz [5], Kowalczyk and

Buxmann [6]

Decisions of manager Ghazanfari et al. [16], Khodaee et al. [7], nd

Williamse and Williamse [17]

On-Line Analytical Processing (OLAP) On-Line Transaction Processing (OLTP)

Data Warehousing (DW) Data Mining (DM)

The use of information and analytical tools The organization's readiness to deploy business

intelligence system

On-Line Analytical Processing (OLAP) On-Line Transaction Processing (OLTP)

Data Warehousing (DW) Data Mining (DM)

Intelligent Decision Support System (IDSS) Intelligent Agent (IA)

Knowledge Management System (KMS) Supply Chain Management (SCM)

Customer Relationship Management (CRM) Enterprise Resource Planning (ERP)

Enterprise Information Management (EIM)

The use of information and analytical tools The organization's readiness to deploy business

intelligence system Culture of continuous process improvement

Culture methodical decision making and process engineering

Organization and Information Technology Technical preparation systems, business

intelligence and data warehousing Strategic alignment of business and IT

Portfolio management

Increasing the decision-making process knowledge

Decision-making capacity to handle large or complex issues

Ability to solve large and complicated problems Helping carry out exploratory analysis and

historical trend analysis Create new options in the decision (an

alternative) Increased funding decisions based on accurate

and sufficient information Improve communication between interdependent

individuals in decisions (decision chain)

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Improving inter-agency communications between people in decision making

Improve coordination of the decision by manager Satisfaction the outcome of the decision

Employee participation in decision-making decentralized system

Reduce time in the organization's decision- making process

Reduce the cost of decision-making in the organization

In this research, we will evaluate the existing literature and consider previous findings in order to evaluate the role of management information systems and business intelligence and also identify success factors for these systems. A new perspective can be obtained about the role of information systems in management and business intelligence and a new step can be taken in design of prospective strategies for creation of new competitive advantages by implementing the success factors of these systems using the results of this study. In fact, the most important purpose of this research can be considered as “designing support system of business intelligence decision making in order to increase the effectiveness in decision making process of managers in service providing companies”. The importance and necessity of such a research can be noted according to criteria such as development of knowledge about the issues of business intelligence in order to increase the effectiveness of decision-making process of managers as well as the absence of a system for providing recommendations for managers in making decision about business intelligence issues.

Research Method Since design researches have their own unique methodology, a combination of critical theory and design science research approach have been used in this research by evaluation of the main paradigms of philosophical grounding for social and management science researches and research method for information systems. In fact from the perspective of ontology of critical research paradigm, facts and issues in this research which deal with implementation of business intelligence to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company based on scientific documentation of organizational IT industry which are surrounded by social, political, cultural, economic, moral and other factors which are affecting decisions relating to the implementation of business intelligence in order to increase the effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company based on scientific documentation of organizational IT industry become transparent over time and in interactions with members of organization. In fact, this is a practical Research because its results and findings are used to solve issues related to the implementation of business intelligence in order to increase the effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company based on scientific documentation of organizational IT industry which is one of the specific problems of the company. On the other hand, philosophical

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assumptions use alternative situations with technological - social theme for science research approach from the perspective of ontology. From the perspective of epistemology, the researcher in this study comprehensively evaluates the studied issue by interaction with experts in this field and experts provide their opinion about correctness and relevance of the concepts and principles in tools for determination of decision-making components. Here, subjectivity and values of experts in the field of study will affect the issue. Epistemology in research approach of science in this research refers to two cases: One is becoming aware by designing decision-making support system based on the principle for implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company using fuzzy logic and the other is limited objective structures within the context of implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company. In terms of value, this research is about creation of a new knowledge in the field of implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company, improvement in business intelligence deployment status in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company, understanding the business intelligence implementation issues in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company. Advantage of design research strategy and its creation in the field of information systems is its attention to technical aspects of IT products based on assumptions about the nature of the universe and method of understanding those. Here, models produced by the designer, are true representatives of the truth and the designer uses logical thinking and mathematical and logic-based tools and methods instead of politics and human intuition for this task. Outputs of research approach for designing science can be one of the following: structures (conceptual vocabulary of a scientific field), models (a set of proposals or statements expressing relations between structures), Methods (a set of steps used to perform a task), prototyping idea (making models, structures and methods real and operational) or a better theory (creating artifacts comparable to natural laboratorial science). In short, steps for a research based on research approach of designing science are as follows: awareness about the problem, guessing (designing prototype), development (creating artifact), and evaluation (system performance measures), and conclusion (final outputs and results). Since the interactive nature of this research requires discussion between researcher and experts in the studied field, Misunderstandings and omissions of researcher are solved. This is a descriptive – evaluation study in terms of method because it precisely describes concepts and rules related to the implementation business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company on one hand and the relation between these concepts and rules are evaluated and determined by expert on the other hand. The library studies have been carried out by referring to the Internet, studying researches, and books, articles in national and international journals and studying statistics and documents published by the University. Also, researcher made tool for gathering information, interviews with IT experts, staff and administrators of university

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and IT companies and university professors have been intended for field studies. The need for observations and interviews are also among the necessities of evaluation in this research. Due to the use of articles and documents from different sources related to the implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company, the data collection method in this research is "case study of documents" and tools to determine components of decision-making and Interview model have been used to evaluate the principles of support system for decision making based on the principle to implement business intelligence in order to increase the effectiveness of decision- making process of managers in Saman Kish Electronic Payment Company which are extracted from the opinions of experts. The timeline of the present study is as follows: this research started in August 2016 and its duration was 6 months and it ended in January 2016. It is necessary to separately predict all activities and implementation phases of research (including the time of periodical reports) and time required for each and those listed in related tables and are observed as much as possible during the research. Since a research process requires at least several months of effort, maximum advantage must be taken from the spent time. The scope of this study is organizational IT industry. The logical criteria to prepare and set the conceptual model of research is the principle of information richness which means that the researcher considerers considerations, facilities and research time continues to collect theoretical data in the field of components affecting the implementation of business intelligence in order to increase the effectiveness of the decision-making process of managers and continues to evaluate and study domestic or foreign resources until the collecting information are repeated and vicious cycle begins. After evaluations in the field of components affecting the implementation of business intelligence in order to increase the effectiveness of the decision-making process of managers, the most important components and indicators affecting implementation of business intelligence in order to increase the effectiveness of the decision-making process of managers have been presented in the Figure 1 below in form of the theoretical framework of research. It is obvious that these components and indicators derived from the theoretical principles are in form of an initial model which must be evaluated by experts in order to be able to achieve the final research model by further processing: With respect to the application of fuzzy decision support system designed in this study, after reviewing the structure of research systems and at the end, five steps have been considered for designing support system for decision making based on principle in order to implement business intelligence based on fuzzy logic which are as follows (Figure 2) [18-20]:

1. Modeling the concepts in the field of business intelligence implementation in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company for identification of input and output components and drawing relations between them.

2. Defining qualitative components using linguistic constraints and allocation of numbers and fuzzy sets and membership functions to them.

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3. Designing support system for Fuzzy decision making based on definitions and designs using MATLAB software: this step includes extracting the rules of practice and assessment by experts and creation of base for fuzzy rules as well as designing inference engine with access to fuzzy rules.

4. Designing user interface and method of display for options and method of using the designed support system for fuzzy decision making.

5. Selection of a method for defuzzification in order to convert numbers and fuzzy sets to definitive values to evaluate the actual performance of the system.

Figure 1: Conceptual Model.

Figure 2: Structure of Fuzzy Decision Support System (BI+FDSS).

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“Implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company” determines the relation between components and method of this relation in decision- making model of the research. A good theoretical framework should include all components and method of their relation with each other. The relation between dependent and independent variables are initially determined in form of proposal in the initial model of research: in the present study, component is a feature or factor which is common between people in society and can have different quantities and different values. Components are factors which are measured or assessed. In fact, the input variables of support system for fuzzy decision making in the present research are as follows: The first input component: "quality of business intelligence implementation", the second input component: “operational level of business intelligence”, the third input component: “tactical level of business intelligence", the fourth input component: “business intelligence techniques to facilitate decision-making”, the fifth input component: “strategic level of business intelligence” and output component of support system for fuzzy decision making is the status of “effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company”. We compared outputs and responses of “principle-based decision making support system to implement business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company” using the average of experts’ opinions in the evaluated field using a separate tool in order to validate principle-based decision making support system to implement business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company. The following Table 2 shows validation tool for principle-based decision making support system to implement business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company (BI+FDSS) to evaluate the responses of research system: Table 2: System Validation Tool BI+FDSS.

R u

le

Components of the system input BI+FDSS The output component of BI+FDSS

Other Comments

Status of quality of business

intelligence implementation

Status of operational

level of business

intelligence

Status of tactical level of

business intelligence

Status of techniques to facilitate decision- making in business

intelligence

Status of strategic level of

business intelligence

Status of increase the effectiveness of decision-

making process of managers

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DATA ANALYSIS AND SYSTEM DESIGN The study population included in this study can be divided into two general groups: the first group consists of experts and the second group consists of those working in the field of business intelligence in Saman Kish Electronic Payment Company or similar positions in Saman Kish Electronic Payment Company. In the end, the sample size for this research consists of 30 available experts willing to cooperate who were selected using a combination of Purposive non-probability (judgment) sampling and snowball sampling. Data related to the first set of measuring tools (tools to measure the effect of variables in order to increase the effectiveness of decision-making process of managers) were collected in December 2016 and data related to the second set of measuring tools (tools to validate “support system for decision making based on the principle of business intelligence implementation in order to increase the effectiveness of decision-making process of managers”) were collected in late December 2016 (Table 3). The Pearson correlation coefficient based on the criteria of variables used in the research has been used in the present research to evaluate the impact and effectiveness between dependent variable and independent variables. Table 3: a) The correlation between variables. b) Correlations between variables.

The correlation between variables

The correlation between the

variables

The correlation between " Techniques to facilitate decision-making in business intelligence"

OLAP OLTP DW DM IDSS IA KMS SCM CRM ERP EIM

OLAP

correlation coefficient

1 0.476** 0.492** 0.562** 0.796** 0.417* 0.777** 0.479** 0.873** 0.447* 0.550**

Sig. 0.008 0.006 0.001 0.000 0.022 0.000 0.007 0.000 0.013 0.002

OLTP

correlation coefficient

0.476** 1 .887** 0.927** 0.428* 0.845** 0.645** 0.782** 0.538** 0.333 0.641**

Sig. 0.008 .000 0.000 0.018 0.000 0.000 0.000 0.002 0.072 0.000

DW

correlation coefficient

0.492** 0.887** 1 0.960** 0.426* 0.868** 0.678** 0.820** 0.555** 0.253 0.755**

Sig. 0.006 0.000 0.000 0.019 0.000 0.000 0.000 0.001 0.178 0.000

DM

correlation coefficient

0.562** 0.927** 0.960** 1 0.505** 0.918** 0.738** 0.858** 0.622** 0.243 0.725**

Sig. 0.001 0.000 0.000 0.004 0.000 0.000 0.000 0.000 0.197 0.000

IDSS

correlation coefficient

0.796** 0.428* 0.426* 0.505** 1 0.340 0.788** 0.453* .875** 0.658** 0.523**

Sig. 0.000 0.018 0.019 0.004 0.066 0.000 0.012 .000 0.000 0.003

IA

correlation coefficient

0.417* 0.845** 0.868** 0.918** 0.340 1 0.615** 0.779** .484** 0.120 0.646**

Sig. 0.022 0.000 0.000 0.000 0.066 0.000 0.000 0.007 0.527 0.000

KMS

correlation coefficient

0.777** 0.645** 0.678** 0.738** 0.788** 0.615** 1 0.634** 0.905** 0.439* 0.740**

Sig. 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.015 0.000

SCM

correlation coefficient

0.479** 0.782** 0.820** 0.858** 0.453* 0.779** 0.634** 1 0.540** 0.174 0.561**

Sig. 0.007 0.000 0.000 0.000 0.012 0.000 0.000 0.002 0.357 0.001

CRM

correlation coefficient

0.873** 0.538** 0.555** 0.622** 0.875** 0.484** 0.905** 0.540** 1 0.533** 0.627**

Sig. 0.000 0.002 0.001 0.000 0.000 0.007 0.000 0.002 0.002 0.000

ERP

correlation coefficient

0.447* 0.333 0.253 0.243 0.658** 0.120 0.439* 0.174 0.533** 1 0.371*

Sig. 0.013 0.072 0.178 0.197 0.000 0.527 0.015 0.357 0.002 0.044

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EIM

correlation coefficient

0.550** 0.641** 0.755** 0.725** 0.523** 0.646** 0.740** 0.561** 0.627** 0.371* 1

Sig. 0.002 0.000 0.000 0.000 0.003 0.000 0.000 0.001 0.000 0.044

Correlations between variables

Strategic level of business intelligence Strategic level of

Business Intelligence

tactical level of business

intelligence

operational level of business intelligence

strategic level of business intelligence

Pearson correlationcoefficient 1 .763** .875**

Sig .000 .000

tactical level of business intelligence

Pearson correlation coefficient .763** 1 .708**

Sig. .000 .000

operational level of business intelligence

Pearson correlation coefficient .875** .708** 1

Sig. .000 .000

As it can be observed in Table 3 which is related to correlation between variables of research, since the sign of correlation coefficient is the slope of regression line, there is a positive and significant relation between "strategic level of business intelligence” and "technical level of business intelligence" because the Pearson correlation coefficient between them is equal to 0.763. On the other hand, there is a positive and significant relation between "strategic level of business intelligence” and” operational level of business intelligence" because the Pearson correlation coefficient between them is equal to 0.875. On the other hand, there is a positive and significant relation between " operational level of business intelligence” and” technical level of business intelligence" because the Pearson correlation coefficient between them is equal to 0.708. In fact, in can be concluded based on the high correlation between the levels of business intelligence which are A) strategic level of business intelligence (increasing organizational performance and optimizing processes, focusing on financial characteristics, focusing on other important factors in the increased business, focusing on external processes of organization) B) technical level of business intelligence (following activities up, making medium term decisions, providing periodic reports of the process, providing the overall picture of the organization's activities for managers) C) operational level of business intelligence (monitoring business activities, providing information of business processes, making short-term decisions in conducting business activities, the highest concentration in conducting internal business processes) that the decision-making process of managers can become comprehensively effective by analyzing the "business intelligence levels" because “strategic level of business intelligence”, " tactical level of business intelligence” and “operational level of business intelligence” have a significant impact on increasing the effectiveness in decision- making process of managers in Saman Kish Electronic Payment Company. It can be observed in evaluation of the effect of “business intelligence techniques to facilitate decision making" on increasing the effectiveness in decision-making process of managers in Saman Kish Electronic Payment Company that there is a significant positive relation between "OLAP" and "IDSS" in increasing the effectiveness in decision- making process of managers because the Pearson correlation coefficient between them is equal to 0.796. On the other hand, there is a significant positive relation between "OLAP" and “KMS" in increasing the effectiveness in decision-making process of

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managers because the Pearson correlation coefficient between them is equal to 0.777. On the other hand, there is a significant positive relation between "OLAP" and “CRM" in increasing the effectiveness in decision-making process of managers because the Pearson correlation coefficient between them is equal to 0.873. In fact, there is a positive and significant relation between "OLAP" and "DM" to increase the effectiveness of managers in the decision-making process because the Pearson correlation coefficient between them is equal to 0.562. Thus, it can be concluded that evaluation of the effect of “business intelligence techniques to facilitate decision making" can increase the effectiveness in decision-making process of managers in Saman Kish Electronic Payment Company. The supporting system for decision making based on principle of business intelligence implementation will be provided in the present research for the first time in the research field related to the topic to increase the effectiveness of the decision-making process in Saman Kish Electronic Payment Company using fuzzy logic entitled BI+FDSS. In fact, BI+FDSS system is a system which can have inaccurate input data which means the input data of a fuzzy system is in form of a fuzzy set or fuzzy numbers. On the other hand, processes of a fuzzy system can be done inaccurately. One of the most famous and useful inaccurate processes in fuzzy Systems is the use of fuzzy rule base. Each rule in fuzzy rule base is defined with "if - then" structure. With respect to the application of support system for fuzzy decision making designed in this study, five steps have been considered for design of support system for fuzzy decision making for implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company which are: First Step Identification of system input and output variables: we acted on defining input and output variables of support system after finalization of the conceptual model of support system for decision making. Input variables of support system for decision making based on the principle of business intelligence implementation in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company using fuzzy logic entitled BI+FDSS are: "quality of business intelligence implementation "; “operational level of business intelligence"; “tactical level of business intelligence"; “business intelligence techniques to facilitate decision-making" and “strategic level of business intelligence" and the output variable of the mentioned system is “implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company”. The input and output variables of support system for decision making can be shown as follows based on conceptual model and applying the opinions of experts. Second step: defining qualitative variables using language constraints and allocation of fuzzy numbers and sets and membership functions: table and figure of linguistic variables show fuzzy values and triangular and trapezoidal numbers membership functions associated with the input and output variables of support system for decision making in triple and quintet spectra (Table 4, Figures 3 and 4).

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Figure 3: Model of module input variables "to implement business intelligence in order to increase the effectiveness of decision-making process in managers".

Table 4: linguistic variables associated with module output variable "implementation of business intelligence for effective the decisions made by managers".

linguistic variable Equivalent to English

Triangular and trapezoidal membership functions

Very weak Very Weak (0 0 0.03 0.15)

Weak Weak (0.1 0.2 0.3)

Medium (normal) Medium (0.3 0.5 0.7)

Good Good (0.7 0.8 0.9)

Excellent Excellent (0.85 0.97 1 1)

Figure 4: Classification of decision support system research output variable (triangular and trapezoidal membership functions).

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The Third Step Designing knowledge base of support system for decision making: this step includes the rules of extracting expertise and assessment by experts and creation of fuzzy rules base. Fuzzy rules base is a set of "if-then" rules which is considered as the heart of BI+FDSS system because the rest of fuzzy system components are used effectively and efficiently for implementation of these rules. Here, we have considered similar probability for different states between the main variables of support system for decision making. The starting point to create a knowledge base based on rules in a fuzzy system is obtaining a set of "if-then" rules from experts or the knowledge in the evaluated field. The next step is combining these rules in a single system. The method to create rules for knowledge base of the main module in BI+FDSS system is as follows: “implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company” can be evaluated in different states based on weight of each of the input variables of support system for decision making. Here, we have considered similar probability for different states between the main variables of support system for decision making (Table 5). In fact, we can create fuzzy rules based on the following terms and conditions after interviews with experts in the evaluated field. Table 5: How to calculate the weight of possible states rule in the knowledge base for decision support system.

The possibilities for the production of base The weight of each variable × variable definitive amount

Language

given weight

If Status "implement quality of business intelligence" is low (high risk)

0.15 × 0.202 (Has an inverse relationship (1 to

0.5)

0.0303

And "operational level of business intelligence" in normal condition

0.5 × 0.196 ((Has an inverse

relationship (1-.5))

0.098

And 'tactical level of business intelligence "is good

0.85 × 0.198 0.1683

And " techniques to facilitate decision making of business intelligence " is good

0.85 × 0.205 0.17425

And " strategic level of business intelligence" is normal

0.5 × 0.199 0.0995

Then; The "effectiveness of the decision-making

process I in managers of Kish payment electronic company" is at what level?

weighted average assumptions: 0.57035

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Based on the membership functions of linguistic variables by experts in Table 5, 0.570 are in range defined for linguistic variable of "average (normal)". Thus, the "effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company” in above conditions will be "Medium (normal)". Other rules of knowledge base of this support system for decision making have also been created in this way. In the end, the number of fuzzy rules modules of “implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company” in BI+FDSS system is equal to 243 due to existence of five main variables that each had 3 modes. The following Figure 5 is related to Fuzzy rule databases of BI+FDSS module system. Figure 5: Method of creating fuzzy rules in the knowledge base for module of “implementation of business intelligence in order to increase the effectiveness of decision-making process of managers.

The Fourth Step Designing the inference engine of BI+FDSS system: in this step, Centroid method has been used for defuzzification to transform fuzzy numbers and fuzzy sets to definitive numbers to evaluate the actual performance of the system. MATLAB software can be used to have inference based on rules in knowledge base of BI+FDSS payment system. In fact, the he main reason for using Mamdani inference engine (instead of Sugeno) is that selection of type of requirement and aggregation of fuzzy rules (in order to collect fuzzy rules for inference and conclusion) has been deactivated in Sugeno inference engine. Prod is used in MATLAB software to select the type of requirement because Min operator makes the output fuzzy set short and incomplete. Defuzzification mechanism in the BI+FDSS system turns fuzzy output into a certain number. Central method is used MATLAB software in defuzzification because

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this method of defuzzification reduces the complexity of the problem and leads to less time for calculations. Here, we select "Sum" aggregation method for fuzzy rules due to connected fuzzy rules due to "And" operator. In this case, the more accurate set of output rules are considered and not their maximum. The Fifth Step Describing the method of using support system for decision making and analyzing its outputs: the outputs of BI+FDSS system can be considered in form of numbers (accurate) and in linguistic form in order to analyze the behavior of the system output variable of “implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company”. The following Figure 6 analyzes the behavior of input and output variables of module of BI+FDSS system. Figure 6: Analyzing the behavior of output variable in form of numbers (accurate) and in linguistic form based on 5 input variables.

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Here, we can use the outputs of BI+FDSS system to analyze “the effectiveness of the decision-making process in Saman Kish Electronic Payment Company” based on variables such as “business intelligence techniques to facilitate decision making”, “strategic level of business intelligence", “tactical level of business intelligence", “operational level of business intelligence" and “quality of business intelligence implementation". For example: If the condition of "implementation quality of business intelligence" is weak and “operational level of business intelligence" is in normal condition and “tactical level of business intelligence" is good and “business intelligence techniques to facilitate decision making” is good and “strategic level of business intelligence" is normal, then” the effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company” will be at its third level which is "Medium (normal)". In other words, we can use support system for decision making designed in this research to numerically and more precisely evaluate the “effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company”: If the condition of "implementation quality of business intelligence" is weak and is exactly 00:15 and “operational level of business intelligence" is in normal condition and exactly 0.5 and “tactical level of business intelligence" is good and exactly 0.85 and “business intelligence techniques to facilitate decision making” is good and exactly 0.85 and “strategic level of business intelligence" is normal exactly 0.5, , then” the effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company” will be at "Medium (normal)" level which is exactly 0.570. Outputs and results of decision support system have been separately compared with opinions of 18 experts after its design, the results of which can be observed in the following Table 6 based on the rules of decision support system and average response of experts. Table 6: Information on comparing the outputs of “BI+FDSS System" with an average opinion of experts.

Rules of decision support system

Output of decision

support system

Average experts

responses Difference ratio

Final difference

Rule. 3 1 1.22 0.22/4=0.055

0.06475

Rule. 45 3 2.72 0.28/4=0.0675

Rule. 79 3 2.78 0.22/4=0.055

Rule. 86 2 1.67 0.22/4=0.0825

Rule. 103 2 1.67 0.22/4=0.0825

Rule. 140 3 2.78 0.22/4=0.055

Rule. 157 3 3 0/4=0

Rule. 219 2 1.94 0.06/4=0.015

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Rule. 224 2 1.39 0.61/4=0.1525

Rule. 235 2 1.78 0.22/4=0.0825

We can compare decision support system outputs in this system which are BI+FDSS with based on the information described in the Table 6 above average opinion of experts based on the information described in the Table 6 above. Since the opinions of experts have been expressed in form of 5-point Likert spectrum (1 to 5), the difference between decision support system outputs in this research which are BI+FDSS and average opinion of experts is not significant and is equal to 0.06475 (Table 7). Since there is no sufficient reason for accepting the null hypothesis, the alternative hypothesis is accepted which means there is no significant difference between decision support system outputs in this research which are BI+FDSS and average opinion of experts. Table 7: Comparison of the most relevant studies in the theoretical literature with findings in the present research.

No Research title Referenc

e

Compare results

Investigating the "

techniques to facilitate

decision making of business

intelligence"

The study "business intelligenc e levels"

Study the "implementatio n of business intelligence"

Managers focus on

the decision- making process

Decision Support System

Fuzzy Logic

Validation System

Case Study

1

In order to increase the effectiveness of the implementation of

business intelligence in decision-making

executives in the Saman Kish Electronic Payment

company

Zamani, (study)

* * * * * * * *

2

Identify and prioritize the critical success factors in

the implementation of business intelligence systems using AHP Method Case Study: Small and medium

companies

Badizadeh et al. [21]

* * - * - * - *

3

Approaches use of business intelligence to

improve decision-making bank managers (case study Samen credit

institution)

Falah et al. [12]

- * * * - - - *

4

Business Intelligence Application Development as a decision support tool

in the banking system

Naderlo and Naderlo [10]

- * * * - - - *

5

The impact of BI maturity on the use of information

systems in business processes according to the analytical decision- making culture among

managers of Bank

Saderat Iran

Mollaei, 2014 - * * * - - - *

6

Design of decision support system for

employee performance evaluation Case Study on

Saderat Bank of Iran

Jalalian et al. [22]

- - - * * * * *

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7

Development and validation of a rule-based

time series complexity scoring technique to

support design of adaptive forecasting DSS

Adya and Lusk [20]

- - - - * * * *

8

An ambidextrous perspective on business intelligence and analytics

support in decision processes: Insights from

a multiple case study

Kowalczyk and Buxmann.

[6] * * - * - - - *

9

The Impact of Business Intelligence on the Quality

of Decision Making – A Mediation Model

Wieder and Ossimitz [5]

* * - * - * - *

10

Social Business Intelligence: A New

Perspective for Decision Makers

Muntean et al. [15]

* * - * - - - *

11

Towards business intelligence systems success: Effects of

maturity and culture on analytical decision

making

Popovič [23] * * - * - * - *

CONCLUSION One of the most important results of research based on “designing decision support system based on principle of business intelligence implementation in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company using fuzzy logic” is that since the sign of correlation coefficient is the slope of regression line, there is a positive and significant relation between "strategic level of business intelligence” and "technical level of business intelligence" because the Pearson correlation coefficient between them is equal to 0.763. On the other hand, there is a positive and significant relation between "strategic level of business intelligence” and” operational level of business intelligence" because the Pearson correlation coefficient between them is equal to 0.875. On the other hand, there is a positive and significant relation between "operational level of business intelligence” and” technical level of business intelligence" because the Pearson correlation coefficient between them is equal to 0.708. In fact, in can be concluded based on the high correlation between the levels of business intelligence which are A) strategic level of business intelligence (increasing organizational performance and optimizing processes, focusing on financial characteristics, focusing on other important factors in the increased business, focusing on external processes of organization) B) technical level of business intelligence (following activities up, making medium term decisions, providing periodic reports of the process, providing the overall picture of the organization's activities for managers) C) operational level of business intelligence (monitoring business activities, providing information of business processes, making short-term decisions in conducting business activities, the highest concentration in conducting internal business processes) that the decision-making process of managers

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can become comprehensively effective by analyzing the "business intelligence levels" because “strategic level of business intelligence”, "tactical level of business intelligence” and “operational level of business intelligence” have a significant impact on increasing the effectiveness in decision-making process of managers in Saman Kish Electronic Payment Company. It can be observed in evaluation of the effect of “business intelligence techniques to facilitate decision making" on increasing the effectiveness in decision-making process of managers in Saman Kish Electronic Payment Company that there is a significant positive relation between "OLAP" and "IDSS" in increasing the effectiveness in decision-making process of managers because the Pearson correlation coefficient between them is equal to 0.796. On the other hand, there is a significant positive relation between "OLAP" and “KMS" in increasing the effectiveness in decision- making process of managers because the Pearson correlation coefficient between them is equal to 0.777. On the other hand, there is a significant positive relation between "OLAP" and “CRM" in increasing the effectiveness in decision-making process of managers because the Pearson correlation coefficient between them is equal to 0.873. In fact, there is a positive and significant relation between "OLAP" and "DM" to increase the effectiveness of managers in the decision-making process because the Pearson correlation coefficient between them is equal to 0.562. Thus, it can be concluded that evaluation of the effect of “business intelligence techniques to facilitate decision making" can increase the effectiveness in decision-making process of managers in Saman Kish Electronic Payment Company. Here, we can use the outputs of BI+FDSS system to analyze “the effectiveness of the decision-making process in Saman Kish Electronic Payment Company” based on variables such as “business intelligence techniques to facilitate decision making”, “strategic level of business intelligence", “tactical level of business intelligence", “operational level of business intelligence" and “quality of business intelligence implementation". The Table 7 compares the most important results and findings in the present research with results and findings of relevant studies in the theoretical literature. Given the fact that Saman Kish Electronic Payment Company provided the means of contactless payment for the clients as the first Internet payment service provider in the banking system, evaluation and analysis of research variables which are “business intelligence techniques to facilitate decision making”, “strategic level of business intelligence", “tactical level of business intelligence", “operational level of business intelligence" and “quality of business intelligence implementation" and “effectiveness of the decision-making process of managers in Saman Kish Electronic Payment Company” can improve the decision-making process of managers in Saman Kish Electronic Payment Company in main fields of activity of this company as follows: Providing e-commerce services, installation and support of Card readers, Providing payment services via mobile phone. According to above discussion, the most important recommendations for further researches are as follows:

 Using other artificial intelligence techniques especially artificial neural network and the most important and most relevant algorithms in the field of artificial intelligence in order to increase the richness of the content of the mentioned system

 Using Fuzzy multi-criteria decision making techniques (MCDM) for network

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ranking of relations between model for implementation of business intelligence in order to increase the effectiveness of decision-making process of managers in Saman Kish Electronic Payment Company

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5. Wieder B, Ossimitz ML (2015) The Impact of Business Intelligence on the Quality of Decision Making – A Mediation Model. Procedia Computer Science, 64: 1163- 1171.

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7. Khodaee, Atie, Davood KM (2014) Feasibility study on the implementation of business intelligence in the insurance industry. Insurance Journal magazine (insurance industry): Winter 2014 29: 165-187.

8. Esmaeel AM (2010) The effect of information technology on business intelligence managers. Business management magazine: Spring 2010 2: 11-29.

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business intelligence software in Iran. Enterprise resource management research publication: Spring 2012 2: 21-43.

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20. Adya M, Edward JL (2016) Development and validation of a rule-based time series complexity scoring technique to support design of adaptive forecasting DSS. Decision Support Systems 83: 70-82.

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Business intelligence report.edited.docx

Business intelligence report

Name

Professor

Course

Affiliation

Date

Abstract

There is a need to apply in addition to undertaking the best utilization in terms of the aspects of the ICT tool within the business intelligence to attain the most efficient decision making within any set organization. This paper seeks to get an understanding on the way that will be used between the business intelligence and manner by which there is more to do in the idea of getting to make the best decision within a set platform. To have an ability to make support of the better decision-making capabilities set into different organizations. Business intelligence can be defined as the idea in which there is more to do in the manner by which it is not only a tool, but it is a system developed to help in the approaches within an organizational structure. The basis, in this case, is in line to the aspects of getting speedy analysis on the information to have the ability to make the best and most accurate decision within any organization set up. In the study, there will be the reviews of a different journal to examine how there will be the ability to understand the ways that will be used to make do the aspects of getting the best decision in the business intelligence sector.

Introduction

Reference 1

Title - de Castro Peixoto, L., Golgher, A.B. and Cyrino, Á.B., 2017. Using information systems to a strategic decision: An analysis of the values added under executive's perspective. Brazilian Journal of Information Science: research trends, 11(2).

The journal has undertaken the best examination about the topic associated with the idea of the business intelligence roles on the issues of the strategic decision-making process. In the present word, the issues of technology have been on the rise with new invention getting to be presented with every day dawn. This has assisted in making better the opportunities to solve a complicated problem that is presented into the set scene as well as getting allocate better efficacy. The ability to get better decision making has been made possible by the presence of the BI to attain better abilities about the issues of the competitive environment that are ascertained by the utilization of the idea of business intelligence.[footnoteRef:2] Within this, there has been the usage of the issues to make do better capabilities about the issues of having the decision made being faster and more accurate. [2: de Castro Peixoto, L., Golgher, A.B. and Cyrino, Á.B., 2017. Using information systems to the strategic decision: An analysis of the values added under executive's perspective. Brazilian Journal of Information Science: research trends, 11(2). ]

Business intelligence has been implemented to assist in the allocation of the best decision need within any set organization. The process of decision making is understood as the process that is in relations to getting the ability to have an understanding of the choices they will be in relations to the course of firm goals. In the technology getting best abilities to undertake better capacities when it comes to the issues of decision making will be in relations to the platform of implanting better decision to have the ability to attain best competitive advantages.

The role that is played by the utilization of the issues of business intelligence is in line with the aspects of getting into place better communication channels. The presence of better and diversified platform for which there will be a chance to make the decision-making process has been crucial within many organizations. This has also assisted in the elevation of the speed used by an organization to make the decision in relating to major issues and even come up with the best solution to all the problem that comes up in an organization setting.

Having business intelligence being applied in the activities of decision making can be accrued to having into place better abilities to make do the analysis of information that is presented into an organization, the presence of an arena from which information can be assessed has proved to be the best in that there is the chance to get better decision-making process it places within the organization. In this case, hence there is the chance to get different approaches too in the organization.

Reference 2

Title - Harrison, R., Parker, A., Brosas, G., Chiong, R. and Tian, X., 2015. The role of technology in the management and exploitation of internal business intelligence. Journal of Systems and Information Technology.

The journal has discussed the roles that have been allocated and played by the topic of business intelligence within the arena associated with decision making within the presented day world view of issues. In this case, thus, there has been a change in the level of tech development in the global setting. In this case, business intelligence has evolved to form the central point of focus that needs to be fully understood to ascertain all the idea researcher and scholars have put forward the. [footnoteRef:3]This article has, however, been able to incorporate all the idea fully and hence allocate the needed know-how in relations to the topic associated to the role played by business intelligence implementation into decision making within a set platform. [3: Harrison, R., Parker, A., Brosas, G., Chiong, R. and Tian, X., 2015. The role of technology in the management and exploitation of internal business intelligence. Journal of Systems and Information Technology. ]

There has been the result presented from diverse researchers in the past time about the level which business intelligence has been growing in terms of importance. In this case, thus, BI has been found by the researcher to be forming a central point that needs to be focused and understood fully. This will help in businesses getting to yield more a better chance to be much prosperous in operation. Business intelligence has played the roles of getting into play better decision-making abilities that have been applied to a diverse business platform to help in getting better competitive advantage into the set business scene.

Business intelligence has been growing in term of the level of importance that it has about the present world.[footnoteRef:4] This because a decision at the senior level positions in firms is more inclined to the aspects of getting to incorporate the idea of business intelligence. This is because the newly developed technology has been helping in getting more channels to make better and diverse decisions. [4: Harrison, R., Parker, A., Brosas, G., Chiong, R. and Tian, X., 2015. The role of technology in the management and exploitation of internal business intelligence. Journal of Systems and Information Technology. ]

There has been researching that has been undertaken. The result from the research has been on the factor that, business intelligence and the decision making within firms has been assisted in the manner by which there has been more to do within how there have been abilities to make better the issues of marketing and the manufacturing within the set place in the issues about the decision-making process within any organizations.

The reach paper has stated that there will be most likely positive impacts on the organization about the way by which the business intelligence system will impact the issues in the organizational setting. There will be more in terms of the effectiveness level that will be assumed from the set case. In this case, there will be better abilities to make a better decision within the presented case. The paper in this case; thus, there will be a success from the set platforms, and the organization will have the ability to apply business intelligence in the issues regarding the making of decisions.

Reference 3

Title - Iffat, N., Chaudhry, M.S. and Riaz, A., 2017. Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry (A Case Study of Pepsi Co. Pakistan). Journal of Statistics, 24(1), p.35.

In this paper, there was an examination on the issues associated to the impacts of the utilization of the issue about the aspects of business intelligence and ability to come up with best decision-making levels in any set organizations. Organization are built by the presence of different level of the internal environment that have been affected by a different type of forces. Such factors are about the ideas, and the issues of organizational functionality lie the people, the process and the structural scene of the firm in place.

Business intelligence can be stated to related to the tools of being the centre within an organization is a way such there is need for the organization to have the ability to make do in the best aspects by which there is more to do within the set places of operations. [footnoteRef:5]There is a need to undertake the application of BI within an organization to have the ability to change the manner of operations it sets to the public scene. There is a need for the application to the BI process to have the ability to make do the process of decision making. [5: Iffat, N., Chaudhry, M.S. and Riaz, A., 2017. Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry (A Case Study of Pepsi Co. Pakistan). Journal of Statistics, 24(1), p.35. ]

Scholars have presented decision making as the idea of allocating as well as utilization on the needed funds within an organization in the best manner. In this case, then there is a need to have better BI into the organization system to assist in the processes affecting decision making. The journal has presented the issues on the case such that there is more do in the manner by which there is a need for an increase in the level of growth within the set firms.

Business intelligence has assisted in many organizations to have the ability to get into play, different activities within the set firms to have a purpose of attaining information about the day to day operation of the organization. This is to have issues about the decision-making process within the set organization. The utilization of BI as per the scholars of the journal stets that this can be the best way used to have the ability to ascertain better abilities to incorporate the issues of making the best decision in the firms. This will be following undertaking a comparison on the ways used to make do certain obligations in different set idea and platforms.

The roles of business intelligence within a set organization is in association with getting into play the best idea when it comes to the level of being constructive within the set organization.[footnoteRef:6] There will be the platform presented for the BI to run the cloud; hence there will be more in terms of the efficacy level attained from the set objectives. In this case, the scholarly article has presented BI as one of the most powerful tools used in undertaking decision making within the set organization presented into the set case. [6: Iffat, N., Chaudhry, M.S. and Riaz, A., 2017. Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry (A Case Study of Pepsi Co. Pakistan). Journal of Statistics, 24(1), p.35. ]

Reference 4

Title – Kulkarni, U., Robles-Flores, J.A. and Popovič, A., 2017. Business intelligence capability: the effect of top management and the mediating roles of user participation and analytical decision-making orientation. Journal of the Association for Information Systems, 18(7), p.1.

The paper has presented the ways by which there has been the development of business intelligence as a system that will be used to make do the idea of getting an organization to get better competitive advantages. [footnoteRef:7]In this case, therefore, there will be more in terms of the decision making getting to be better within the set organization to have the ability to becomes better in the market share accorded to any set organization. The business intelligence system has been taken as a complicated system that is in line to the idea of tech solution needed to attain the best quality in term of the information presented that has been sourced from data stores. All this is geared at the satisfaction of better decision making in the set organization. [7: Kulkarni, U., Robles-Flores, J.A. and Popovič, A., 2017. Business intelligence capability: the effect of top management and the mediating roles of user participation and analytical decision-making orientation. Journal of the Association for Information Systems, 18(7), p.1. ]

The tools within the set tech within the business intelligence platforms are about the ideology of creation of a friendly environment that will allocate the users the timeframe needed to have the chance to get the best access to decision making within the set organization. The decision made within the set firm not only need to be the best but also there is a need to have into place the right decision to avoid the organization getting into a loss of any kind. [footnoteRef:8]However, there has not been a fair level of success in the development of business intelligence platforms. [8: Kulkarni, U., Robles-Flores, J.A. and Popovič, A., 2017. Business intelligence capability: the effect of top management and the mediating roles of user participation and analytical decision-making orientation. Journal of the Association for Information Systems, 18(7), p.1. ]

The paper has investigated how top-level management has applied business intelligence to make a crucial decision affecting the organization wellbeing. The decision that is made into the organization from the article, in this case, is about getting into the best idea the BI models that will present best suited modes. This will form the central part from the scene such that there will be better chances to offset the goals of the organization from the objectives presented.

Reference 5

Title - Zamani, M., Maeen, M. and Haghparast, M., 2017. Implementation of business intelligence to increase the effectiveness of managers' decision-making process in companies providing payment services. The Journal of Internet Banking and Commerce, pp.1-24.

The research has presented the most crucial, level of the ideas as being the level of which there is need to implemented the issues of BI to have the ability make an increment to the efficacies within any organization about can come up with the best ideas associated to decision making within the set environments. The introduction of a platform that will be used to assist in the elevation of the decision-making level within a central organization issues within any set firms. In this case, there is a need for an organization to stay operational and in business. As a result of such hence, it makes it necessary to get the BI into pace to assist in the allocation of best and right decision to attain all the organization goals needed in any set case.

BI in an organization is made up of a set of tools that are interconnected to a central database within the system which is obligated with the activity of formulating the solution to the issues presented into the organization in association for the need to meet set goals.

From the journal, BI is inclusive of a wide variety of business process tech application all geared at helping to attain better decision-making abilities by the utilization data collected and stored as well as undertaken through analysis to get best results.

Manager decision making

Decisions making is an integral part of the senior level of any organization; there is a need for any organizations to have with its operation the best in the abilities allocated to making decisions. There is a need for the BI to be utilized we it comes to the issue associated with decision making within the set organization to be capable of receiving the best product and services.[footnoteRef:9] BI is applied from the strategic level for deciding within any firms. In this case, there is the likelihood to attain more in terms of the elevation in the performance outputs to have the chance to make an optimization of the business processes as well as the decision-making process. [9: Zamani, M., Maeen, M. and Haghparast, M., 2017. Implementation of business intelligence to increase the effectiveness of managers' decision-making process in companies providing payment services. The Journal of Internet Banking and Commerce, pp.1-24. ]

Sales decision making - BI has been applied to make a decision within organizations as well as explore sales trends within different organizations. With this case, there is a better ability to decide within the firms by the BI tool applications.

Devising marketing strategy - this is an idea involving the issues associated with the aspects of getting to make up the best techniques they can be used to enter a certain market place. In this case, the best decision will be made on the techniques useable into a certain market gap. This is through the use of BI.

Financial decision making – application of BI is crucial in this case as it assists in the evaluation of major finances in the structure like getting a balance in the sheet figures and profit margins within the business case.

Executive decision making – some factors entities are presented by BI. Such has proven to be legitimate as they assist the executive in the issues of making a decision that affects the organization success within the platform of operations. [footnoteRef:10]There is also the ability to take a long at the market and create a guide for the executives to make do the best in terms of the issues in along to the aspects of an establishment to a future decision that will be crucial for the organization functioning. [10: Zamani, M., Maeen, M. and Haghparast, M., 2017. Implementation of business intelligence to increase the effectiveness of managers' decision-making process in companies providing payment services. The Journal of Internet Banking and Commerce, pp.1-24. ]

Conclusion

Business intelligence can be used within diverse firms to have the chance to get into place better abilities associated with deciding within organizations. From the examination of the journals, there is the presence of evidence that business intelligence is stated as a fact that is usable in a sense such that is in line to the issues of the assistance needed by the top-level employees to make the best decision affecting the organization operations. Decision making forms a central point of focus on the issues of organization success. In this case, thus, there is a need to have better abilities to attain decision and come to a solution to issues that are affecting the success of the organizations.

References

de Castro Peixoto, L., Golgher, A.B. and Cyrino, Á.B., 2017. Using information systems to a strategic decision: An analysis of the values added under executive's perspective. Brazilian Journal of Information Science: research trends, 11(2).

Harrison, R., Parker, A., Brosas, G., Chiong, R. and Tian, X., 2015. The role of technology in the management and exploitation of internal business intelligence. Journal of Systems and Information Technology.

Iffat, N., Chaudhry, M.S. and Riaz, A., 2017. Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry (A Case Study of Pepsi Co. Pakistan). Journal of Statistics, 24(1), p.35.

Kulkarni, U., Robles-Flores, J.A. and Popovič, A., 2017. Business intelligence capability: the effect of top management and the mediating roles of user participation and analytical decision-making orientation. Journal of the Association for Information Systems, 18(7), p.1.

Zamani, M., Maeen, M. and Haghparast, M., 2017. Implementation of business intelligence to increase the effectiveness of managers' decision-making process in companies providing payment services. The Journal of Internet Banking and Commerce, pp.1-24.

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Draft cop1.edited.docx

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Role of business intelligence on the strategic decision-making process

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Abstract

There are various levels affected by the decision-making issues in the support system in any organization set up. an organization is made of an intelligence structure and the strategic decision they have been put under investigations in this paper. The demands needed to have into place for the issues of the idea is needed to be in line with the aspects of getting to elevate an increment on the investments with issues related to information systems. Business intelligence is defined as an entity associated with the ideas and aspects of getting along the aspects of a collection of tools and tech that involve data analysis and the ideas of the question needed to reach the needed reports and presentations within the presented case aspects.

Introduction

Business intelligence can be stated to be a platform associated with the idea of a collection of tools and tech involving data analysis. [footnoteRef:1]There has been the capacity associated with the ideas of business intelligence assisting in making a better decision within a different organization and attaining better goals [1: De Castro Peixoto, L., Golgher, A.B. and Cyrino, Á.B., 2017. Using information systems to strategic decision: An analysis of the values added under executive’s perspective. Brazilian Journal of Information Science: research trends, 11(2). ]

Business intelligence

This is a general concept and has evolved to become familiar. There exist the ideas associated with getting the idea of tools, databases and applications. [footnoteRef:2]The main project to make do the issues of making a connection between the availability platform of data. [2: Kulkarni, U., Robles-Flores, J.A. and Popovič, A., 2017. Business intelligence capability: the effect of top management and the mediating roles of user participation and analytical decision-making orientation. Journal of the Association for Information Systems, 18(7), p.1. ]

Manager decision making

Importance of business intelligence and role in the decision-making process

Sale decisions

Ability to make better decision regarding sale issues.

Devising marketing strategy

Implementation of better abilities to make do the issues of getting into place the efficient marketing strategy that will need to make do BI to make an enterprise of the promotion within the organizations.[footnoteRef:3] [3: Harrison, R., Parker, A., Brosas, G., Chiong, R. and Tian, X., 2015. The role of technology in the management and exploitation of internal business intelligence. Journal of Systems and Information Technology. ]

Inventory management

There is a way by which there is a need to make the best decision in an organization to have the ability to attain the best competitive advantage. In this case, hence, the idea of BI will be used to make do the management of the inventory within a supply chain platform.

Financial decision making

There has been the utilization of the BI that allocates managers the ability to view as well as undertake an evaluation of the finances and get a balance to the figure, the profits and losses in an organization. In this, there is space to make better decisions.

Executive decision making

Facts presented by BI have been proven to be important in the fact 8that. They make the best out of the executives having the ability to kame future decisions be more of eminence and best within the organization's success.[footnoteRef:4] [4: Zamani, M., Maeen, M. and Haghparast, M., 2017. Implementation of business intelligence to increase the effectiveness of managers' decision-making process in companies providing payment services. The Journal of Internet Banking and Commerce, pp.1-24. ]

Evaluation of the use of business intelligence to attain competitive advantage

Basis for the assessment is about the idea of utilization of several parameters to get into play the best results into the set scene. BI is used to make do better abilities in relation to the aspects of the competitive environment in relation to the platform of having the ability to predict customer predictions.

Conclusion

There is the utilization of BI in a business platform to attain better goals and organization objectives within diverse settings. In the decision-making process, BI has formed a central point of focus the needs to be examined and allocated the best highlight to decide within the set business be the best.[footnoteRef:5] There will also be space to make do concerning the evaluation level for the BI to have better competitive advantages within a set market platform. [5: Iffat, N., Chaudhry, M.S. and Riaz, A., 2017. Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry (A Case Study of Pepsi Co. Pakistan). Journal of Statistics, 24(1), p.35. ]

References

de Castro Peixoto, L., Golgher, A.B. and Cyrino, Á.B., 2017. Using information systems to strategic decision: An analysis of the values added under executive’s perspective. Brazilian Journal of Information Science: research trends, 11(2).

Harrison, R., Parker, A., Brosas, G., Chiong, R. and Tian, X., 2015. The role of technology in the management and exploitation of internal business intelligence. Journal of Systems and Information Technology.

Iffat, N., Chaudhry, M.S. and Riaz, A., 2017. Significance of Business Intelligence System on Quality Decision Making using Analytic Hierarchy Process in Fast Moving Consumer Goods Industry (A Case Study of Pepsi Co. Pakistan). Journal of Statistics, 24(1), p.35.

Kulkarni, U., Robles-Flores, J.A. and Popovič, A., 2017. Business intelligence capability: the effect of top management and the mediating roles of user participation and analytical decision-making orientation. Journal of the Association for Information Systems, 18(7), p.1.

Zamani, M., Maeen, M. and Haghparast, M., 2017. Implementation of business intelligence to increase the effectiveness of managers' decision-making process in companies providing payment services. The Journal of Internet Banking and Commerce, pp.1-24.

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Ahmad571.pdf

Ahmad571 by Ahmad571 Ahmad571

Submission date: 24-Sep-2020 06:37PM (UTC+0800) Submission ID: 1395679327 File name: Draft_cop1.edited.docx (17.47K) Word count: 763 Character count: 4085

1% SIMILARITY INDEX

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0% PUBLICATIONS

1% STUDENT PAPERS

1 1%

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Exclude bibliography On

Exclude matches Off

Ahmad571 ORIGINALITY REPORT

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www2.marilia.unesp.br Internet Source

Ahmad571

by Ahmad571 Ahmad571

Ahmad571

ORIGINALITY REPORT

PRIMARY SOURCES

Ahmad571 (1).pdf

Ahmad571 by Ahmad571 Ahmad571

Submission date: 24-Sep-2020 11:54PM (UTC+0800) Submission ID: 1395867952 File name: Business_intelligence_report.edited.docx (28.85K) Word count: 2942 Character count: 14741

5% SIMILARITY INDEX

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5% STUDENT PAPERS

1 2%

2 1% 3 1%

4 <1% 5 <1%

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Ahmad571 ORIGINALITY REPORT

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Submitted to London School of Business and Management Student Paper

Submitted to Wilmington University Student Paper

Submitted to Icon College of Technology and Management Student Paper

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Ahmad571

by Ahmad571 Ahmad571

Ahmad571

ORIGINALITY REPORT

PRIMARY SOURCES

Coefficients
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
1	(Constant)	2.226	.411		5.422	.000
	BIS	.380	.137	.270	2.779	.007

Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
1	(Constant)	1.280	.556		2.300	.024
	BIS	.268	.141	.191	1.901	.050
	AHP	.366	.149	.246	2.451	.016