Discussion Board

Decision Sciences Volume 51 Number 3 June 2020

© 2019 Decision Sciences Institute

Monetary Rewards, Intrinsic Motivators, and Work Engagement in the IT-Enabled Sharing Economy: A Mixed-Methods Investigation of Internet Taxi Drivers* Ying Hua School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China, e-mail: [email protected]

Xusen Cheng† School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China, e-mail: [email protected]

Tingting Hou School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China, e-mail: [email protected]

Rob Luo School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China, e-mail: [email protected]

ABSTRACT

The IT-enabled sharing economy has enabled the taxi to become an Internet product, forming a popular new phenomenon in people’s daily lives and creating new roles for employees. How the Internet taxi drivers’ work engagement is influenced in the context of the IT-enabled sharing economy has become an interesting new area for IS researchers to explore. Although monetary rewards are important for employees’ behavior and per- formance, extant studies primarily emphasize the crowding-out and crowding-in effects of financial incentives, rather than the influencing mechanism. This article prospects and develops theoretically the effects of monetary rewards and workplace spiritual- ity on work engagement and demonstrates these effects empirically. An analysis of 35 semistructured interviews revealed three intrinsic motivators: stress reduction, job autonomy, and self-efficacy. We propose a structural model based upon motivation crowding theory. Responses to 235 survey responses showed that work engagement can be improved by providing monetary rewards and enhancing workplace spirituality

∗We thank the National Natural Science Foundation of China (Grant No. 71871061), the Fundamental Research Funds for the Central Universities in UIBE (Grant No.CXTD10-06), Program for Excellent Talents in UIBE (Grant No.18JQ04), and the Foundation for Disciplinary Development of SITM in UIBE for providing funding for part of this research. All the authors contributed equally.

†Corresponding author.

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756 Monetary Rewards, Intrinsic Motivators, and Work Engagement

through intrinsic motivators. This research contributes to exploring the mediating role of intrinsic motivators, extends motivation crowding theory to a new research field, and provides a new perspective on work engagement in the context of the IT-enabled sharing economy. Our findings extend the previous research associated with workplace spirituality and the existing knowledge of operations management from the perspective of labor intensity and trade-off between inputs and outputs. [Submitted: January 2, 2018. Revised: February 22, 2019. Accepted: February 25, 2019.]

Subject Areas: Employee Behavior, Internet Taxi Drivers, IT-Enabled Shar- ing Economy, Motivation Crowding Theory, and Monetary Incentives.

INTRODUCTION

In recent years, a growing body of literature has recognized the existence and importance of the IT-enabled sharing economy, a phenomenon born in the new age of the Internet (Botsman & Rogers, 2010; Hamari, Sjöklint, & Ukkonen, 2016; Edelman, Luca, & Svirsky, 2017). The IT-enabled sharing economy refers to “the peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services” (Hamari et al., 2016, p. 2047). With the development of the IT-enabled sharing economy in cities that struggle with population growth and increasing density, the problems of inner-city traffic, congestion, and pollution have largely been reduced (Belk, 2014). An increasing number of information technology-based companies have invested capital in the transportation industry for car sharing services, such as Uber and Didi. The term Internet taxi refers to a new service mode in which private car owners, also known as Internet taxi drivers, provide taxi services through an Internet platform, such as a car-hailing mobile application (app). Although the diverse choice of services benefits taxi passengers by providing a convenient way of calling a taxi, it also causes fierce competition between different taxi platforms for drivers and within the new market share. For Internet taxi drivers, the benefits include a flexible work schedule and a share of commission from each order. However, the increasing number of Internet taxi drivers has brought associated management issues. For instance, owing to a lack of motivation from company management, one group of drivers moved from one Internet taxi platform to other platforms and shared negative comments about the company. It is therefore essential not only for Internet taxi companies to establish ways of motivating drivers to engage in their work but also to investigate this emerging phenomenon.

Economic incentives have increasingly gained prominence in organizational management as a means to adjust intrinsic motivation (Gneezy, Meier, & Rey-Biel, 2011; Dierynck, Landsman, & Renders, 2012; Ederer & Manso, 2013); however, questions have been raised about whether monetary incentives stimulate or damage intrinsic motivation. Motivation crowding theory suggests that external interven- tions could crowd out (undermine) or crowd in (strengthen) people’s intrinsic motivation to engage in work (Osterloh & Frey, 2000). Monetary rewards, as one kind of external intervention measure, could undermine or strengthen intrinsic motivation. For example, if the existence of monetary incentives is seen as a way to control an individual’s autonomy and self-determination, it could undermine

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intrinsic motivation (Warneken & Tomasello, 2008); however, if the existence of monetary rewards is seen as a supportive measure, it could motivate employees to work harder (Osterloh & Frey, 2000). Although motivation crowding theory has been applied to explain the crowding-out and crowding-in effects in differ- ent research fields (Wiersma, 1992; Lin, 2007; Cerasoli, Nicklin, & Ford, 2014), challenges remain in researching Internet taxi drivers’ behavior and the effect of monetary rewards, and little attention has been paid to the role of economic incentives on Internet taxi drivers’ intrinsic motivators.

Although extensive research has been carried out on employee behavior or performance, further studies are needed to consider management procedures, especially in the emerging phenomenon of the IT-enabled sharing economy. Rich, Lepine, and Crawford (2010) observed that work engagement can be seen as a behavioral aspect of employees and that monetary incentives alone do not explain the change in intrinsic motivation. Thus, we argue that workplace spirituality could be an additional source of change in intrinsic motivators and work engagement, given that the effects of workplace spirituality on intrinsic motivators have not yet been closely examined. Workplace spirituality refers to “the recognition that employees have an inner life that nourishes and is nourished by meaningful work that takes place in the context of community” (Ashmos & Duchon, 2000, p. 137). For Internet taxi drivers, such a community can be created through peer to peer or group communication with other drivers using modern mobile technologies such as “WeChat,” thus enabling them to share information about their personal feelings about work, the community, and taxi platforms. When they feel nourished in their work, they might engage more in their work. We applied quantitative dominant mixed methods to answer the following research questions:

(1) What intrinsic motivators of Internet taxi drivers influence their work engagement?

(2) How do monetary rewards and workplace spirituality interact with intrin- sic motivators in determining Internet taxi drivers’ work engagement?

Drawing on motivation crowding theory, this study examines the effect of monetary incentives on user behavior and performance in the context of the IT- enabled sharing economy. We introduce concepts from the psychology field and human resource management to the IS community to help understand this new phe- nomenon. Advances in technology have promoted the IT-enabled sharing econ- omy by building online platforms and creating new job roles for taxi drivers. Those new concepts (i.e., Internet taxi drivers’ intrinsic motivators and Internet taxi drivers’ work engagement) can therefore enable employers to improve the sys- tem of work and manage the Internet taxi drivers effectively, leading to better work performance.

The remainder of this study is organized as follows. The next section presents the theoretical background, followed by the methodology and a discussion of the qualitative and quantitative analyses and the results. Finally, we discuss the con- tributions and limitations of this study and present suggestions for future research.

758 Monetary Rewards, Intrinsic Motivators, and Work Engagement

THEORETICAL BACKGROUND

This section presents the research background and literature review from four aspects: the IT-enabled sharing economy, motivation crowding theory, workplace spirituality, and work engagement.

IT-Enabled Sharing Economy

The IT-enabled sharing economy, a new economic-technological phenomenon born out of the development of information and communications technology, is attracting considerable attention from related business and consumption practices (Botsman & Rogers, 2010; Hamari et al., 2016; Edelman et al., 2017). The increas- ing scarcity of natural resources and the growing awareness of favoring use over possession have given rise to an increase in the IT-enabled sharing economy in various domains, including transportation, tools, and housing (Botsman & Rogers, 2010), and different activities, such as renting, swapping, and trading (Hamari et al., 2016) on different platforms, such as Zipcar, Airbnb, Uber, and Didi. The emergence of mobile taxi apps has facilitated car-sharing behavior and has at- tracted numerous registered users, including passengers and Internet taxi drivers (Cheng, Fu, & Yin, 2017; Cheng, Fu, & de Vreede, 2018).

Recent literature examining the IT-enabled sharing economy has revealed several interesting themes: the conceptual definition of the IT-enabled sharing economy (Belk, 2014), consumer choice and motivation (Möhlmann, 2015; Hamari et al., 2016), online review and trust (Cheng et al., 2019), economic (Zervas, Proserpio, & Byers, 2017), and environmental (Heinrichs, 2013) impacts of the IT-enabled sharing economy. According to Belk (2014), the IT-enabled sharing economy is an economic phenomenon, which emphasizes possession and use over ownership. Engagement and participation in the IT-enabled sharing econ- omy are affected by many factors. For example, Hamari et al. (2016) argued that people are motivated to participate in the IT-enabled sharing economy by its sus- tainability, their enjoyment of the activity, and the economic gains. Additionally, Möhlmann (2015) suggested that utility, trust, cost savings, and familiarity are important factors for choosing a sharing option. The IT-enabled sharing economy has both economic and environmental benefits. Zervas et al. (2017) stated that the IT-enabled sharing economy has become a net producer of new jobs and a source of economic benefits, and Heinrichs (2013) claimed that the awareness of envi- ronmental protection benefits from the engagement of sharing activities. However, research from the perspective of the service provider, such as Internet taxi drivers’ work engagement in the IT-enabled sharing economy, remains limited.

Motivation Crowding Theory

Motivation crowding theory contributes to coordinating the traditional economic model and psychological theories by providing a systematic interaction between two kinds of motivation (i.e., intrinsic motivation and extrinsic motivation) and stipulates the underlying foundation for explaining why monetary incentives do not work as expected in some situations (Osterloh & Frey, 2000). Previous research has used motivation crowding theory to examine the effect of monetary incentives on prosocial behavior (Ariely, Bracha, & Meier, 2009) and employee behavior

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(Dierynck et al., 2012), and on health care (Promberger & Marteau, 2013) and education (Gneezy et al., 2011). Motivation crowding theory suggests that external intervention (monetary incentives or punishment) might undermine (crowd out) or strengthen (crowd in) people’s intrinsic motivation to engage in work (Osterloh & Frey, 2000). Intrinsic motivation refers to “the doing of an activity for its inherent satisfactions rather than some separable consequence” (Ryan & Deci, 2000, p. 56). Extrinsic interventions often emerge as material rewards, either monetary or nonmonetary (Ariely et al., 2009). The distinction between intrinsic motivation and extrinsic interventions is that the former emphasizes the inherent interest of doing something, whereas the latter is unrelated to the nature of the individual or the work.

Intrinsic motivation can play an important role in addressing the issue of performance behaviors (Zhang & Bartol, 2010; Cerasoli et al., 2014). Intrinsic motivation, the psychological need for autonomy and competence (Deci, Koest- ner, & Ryan, 1999), is associated with perceptions of satisfaction and pleasure (Vallerand, 1997; Venkatesh, 2000). Intrinsic motivation arises from the individ- ual’s intrinsic values of the work, relates to the nature of the work, and fosters the individual’s need for self-actualization and self-realization (House & Wigdor, 1967; Amabile, 1993). Previous studies have investigated self-efficacy and per- ceived enjoyment as important intrinsic motivators (Lee, Cheung, & Chen, 2005; Lin, 2007). By emphasizing pleasure and enjoyment as drivers of effort, employees with intrinsic motivation are process focused and consider work the end in itself (Grant, 2008). Compared with individuals motivated extrinsically, intrinsically motivated individuals participate or engage in a task more actively (Cerasoli et al., 2014). Employees with high intrinsic motivation tend to establish close relation- ships with others in work and realize the ethical consequences of their behavior (Tu & Lu, 2016). In this study, we consider intrinsic motivators the influencing factor of intrinsic motivation.

The crowding-out and crowding-in effects in the context of the IT-enabled sharing economy might show the effect of the following psychological mech- anisms: First, if individuals perceive they are controlled, external interventions crowd out intrinsic motivation (Osterloh & Frey, 2000). People with control aver- sion dislike the feeling of being controlled by economic regulation because the need for autonomy and self-determination is not satisfied (Rode, Gómez-Baggethun, & Krause, 2015). Second, if individuals perceive the external interventions to be supportive, external interventions crowd in intrinsic motivation (Osterloh & Frey, 2000). People’s intrinsic motivation increases because of enhanced self-esteem (Rode et al., 2015). Nevertheless, for Internet taxi drivers in the context of the IT-enabled sharing economy, whether external interventions (e.g., rewards) have a positive or negative effect on their intrinsic motivation has not yet been investigated.

Workplace Spirituality

Workplace spirituality has attracted the attention of both academicians and prac- titioners (Cavanagh & Bandsuch, 2002; Gotsis & Kortezi, 2008). However, the definitions of workplace spirituality are inconsistent and elusive. As discussed

760 Monetary Rewards, Intrinsic Motivators, and Work Engagement

above, this study uses the definition of workplace spirituality provided by Ashmos and Duchon (2000).

Workplace spirituality in this research is examined at the individual level, group level and organization level. The individual level refers to meaningful work, the group level refers to the sense of community, and the organization level refers to the alignment with organizational values (Milliman, Czaplewski, & Ferguson, 2003). Previous studies have discussed different dimensions. For example, Ashmos and Duchon (2000) classified workplace spirituality into three components—inner life, meaningful work, and community—which emphasized the individual and group levels. Kolodinsky, Giacalone, and Jurkiewicz (2008) presented three dis- tinct conceptual understandings of workplace spirituality—an individual’s personal spiritual values, the organization’s spiritual values, and the interaction between them—which emphasized the individual and organization levels. However, previ- ous studies of spirituality in sharing behavior are scarce, and they tend rather to emphasize prosocial behavior and the religious aspects of spirituality (Gold, 2003). Very little is currently known about the connection between a wider range of em- ployee behavior and workplace spirituality in the IT-enabled sharing economy.

Work Engagement

Work engagement describes the relationship between an employee and their work, and it relates to employee performance (Salanova, Agut, & Peiró, 2005; Schaufeli, 2013). According to Schaufeli, Salanova, González-Romá, and Bakker (2002), work engagement refers to “a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption” (p. 74). From the perspective of a needs-satisfying approach, work engagement can be conceptualized as the “harnessing of organization members’ selves to their work roles” (Schaufeli, 2013) and where “people employ and express themselves physically, cognitively, and emotionally during role performances” (Kahn, 1990, p. 694). Self-employment and self-expression are important for a person to drive their personal energies into role behaviors (Kahn, 1990). May, Gilson, and Harter (2004) divided work engagement into three dimensions: physical engagement, cognitive engagement, and emotional engagement.

In this study, work engagement refers to the behavioral aspects, measured by physical engagement. The term “physical engagement” was introduced by Kahn (1990) and developed by May et al. (2004) as one of the resources employees bring in role-related tasks and personal energies into role behaviors. Some jobs demand a level of physical exertion or even intense physical challenges (May et al., 2004). Derived from the need to feel competent and maintain autonomy, physical energies are focused on specific work activities (Rich et al., 2010). With increased levels of effort put into work, the physical energy invested facilitates the accomplishment of organizational valued behaviors (Kahn, 1990; Rich et al., 2010). However, although for workers in a labor-intensive industry, physical engagement has been found to be the most important part of work engagement, previous studies have not examined work engagement in relation to the IT-enabled sharing economy. This study aims to provide a view of Internet taxi drivers’ physical engagement.

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METHODOLOGY

This section addresses the procedures and methods used to conduct the qualitative and quantitative research in this study.

Research Design

This study uses a mixed methods design—a combination of qualitative and quanti- tative methods—to develop rich insights into our phenomenon of interest (Harrison & Reilly, 2011; Venkatesh, Brown, & Bala, 2013; Venkatesh, Brown, & Sullivan, 2016). Mixed methods research is useful for addressing confirmatory and ex- ploratory research questions (Teddlie & Tashakkori, 2003; Teddlie & Tashakkori, 2009) and for developing novel theoretical perspectives using a combination of the strengths of both qualitative and quantitative methods (Venkatesh et al., 2013; Venkatesh et al., 2016). Qualitative methods offer an effective way to perform exploratory research to develop a deep understanding of a phenomenon, construct propositions, identify and characterize structures and interactions between com- plex mechanisms, and generate novel theoretical insights (Venkatesh et al., 2013; Zachariadis, Scott, & Barrett, 2013). Quantitative methods are useful in confirma- tory studies for testing theories and causal relationships (Venkatesh et al., 2013; Zachariadis et al., 2013).

In the context of the IT-enabled sharing economy, the phenomenon of Internet taxi drivers who use car-hailing apps emerged and has yet to be explored. In addition, an understanding of the underlying antecedents of a driver’s intrinsic motivation to engage in the work in this new context is lacking. Therefore, Study 1 performs a qualitative analysis to gain in-depth insights into drivers’ intrinsic motivators. To obtain a deeper understanding of the targeted phenomenon by relating complementary findings to qualitative research, a quantitative approach with surveys was employed subsequently to test the research model in Study 2. As presented in Figure 1, Study 1 identified three intrinsic motivators for Internet taxi drivers. Based on the intrinsic motivators established in Study 1 and existing theoretical foundations, Study 2 proposes a research model, which is measured using construct development and validation and tested using structural equation modeling.

Study 1: Qualitative Research

We collected qualitative data from two sources: (1) two pilot interviews with Internet taxi drivers, and (2) 35 semistructured interviews with Internet taxi drivers. The interviews were semistructured and open-ended, which are beneficial for exploring and investigating the Internet taxi drivers’ intrinsic motivators. Initially, we interviewed two Internet taxi drivers to help us modify the interview guide, which we used to conduct 35 interviews.

Two researchers conducted the interviews, which were taped and transcribed; one researcher asked the questions whereas the other made notes and asked sup- plementary questions. The researchers were trained to react to responses rather than shift what seems important because of the difficulty of identifying useful information in the future (Eisenhardt, 1989). All interviews lasted approximately 20 minutes each and were transcribed within 24 hours (Eisenhardt, 1989). The

762 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Figure 1: The relationship between two studies.

interview guide for interviewers comprised three sections: (1) background infor- mation, (2) driving experience and duration, and (3) intrinsic motivators for driving an Internet taxi. We followed the steps described by Miles and Huberman (1994).

The coding process identified three intrinsic motivators: stress reduction, job autonomy, and self-efficacy. Stress reduction, the most frequently mentioned motivator, refers to the decrease of an individual’s subjective evaluation of expe- rienced stress at work and relates to some positive work outcomes (Cavanaugh, Boswell, Roehling, & Boudreau, 2000; Pignata, Winefield, Provis, & Boyd, 2016). For Internet taxi drivers, stress reduction suggests that they feel a decrease in work overload and time pressure. Job autonomy, the second most frequently mentioned intrinsic motivator, refers to the extent of freedom, independence, and discretion in scheduling the work and determining work procedures (Hackman & Oldham, 1975). The third intrinsic motivator that emerged for the Internet taxi drivers is self-efficacy, which can be defined as the confidence in one’s own ability. One be- lieves the resources, skills, and ability possessed are necessary to engage in some specific behaviors (Jones, 1986; Bandura, 1997). Compared with individuals who think they will fail in a task, those ones who think they can perform do better (Gist & Mitchell, 1992). For Internet taxi drivers, their driving skills and familiarity with road conditions contribute to their self-efficacy.

Three sets of intrinsic conditions motivated taxi drivers to use car-hailing apps. Following a data analysis approach used in previous research (French, Luo, & Bose, 2017), we selected the three most frequently mentioned constructs as the intrinsic motivators in this research: stress reduction, job autonomy, and self- efficacy. Table 1 provides sample quotations from the interview data that illustrate each of the most frequently mentioned motivators. Table 2 presents the three intrinsic motivators identified from the interview data.

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Table 1: Data supporting the theme “intrinsic motivator”.

Associated Constructs Representative Quotations

Stress reduction 1. “It is much easier for me since all I need to do is wait for someone to order my service and drive him or her to the destination.”

2. “I wasn’t under any pressure when I began to drive an internet taxi. However, with more and more people flooding into the market and working as drivers, I have become stressed.”

3. “The pressure has certainly decreased. I have more time to relax and be with my family.”

Job autonomy 1. “If you want to earn more, you can work more. But if you want to take a rest, that’s permissible.”

2.“When I drove a traditional taxi, I could choose when to get off work and how long I worked each day. However, I am disturbed by the use of car-hailing apps now.”

3. “If I am busy in the morning, I can go to work in the afternoon. But sometimes the car-hailing apps will allocate me an order far away from my home when I want to get off work, which prolongs my work time.”

Self-efficacy 1. “I have worked as a driver for a long time. I can do the work well, though I always have to concentrate on the road conditions.”

2. “I like driving and chose to be a driver for my job. I like the job and do it well.”

Table 2: Intrinsic motivators for Internet taxi drivers.

Motivator Times Mentioned # of People

Stress reduction 40 29 Job autonomy 28 22 Self-efficacy 16 16

Study 2: Quantitative Research

An empirical study was conducted to explore the effects of monetary rewards and workplace spirituality on work engagement, combined with the findings of three intrinsic motivators concluded from the qualitative analysis. Figure 2 presents the research model and hypotheses.

(1) Hypothesis development

Our research model is based on motivation crowding theory. In the context of drivers’ work with car-hailing apps, workplace spirituality has an impact on intrinsic motivators and work engagement. In line with previous research in the field of behavior (Schaufeli, Bakker, & Van Rhenen, 2009; Bakker, Demerouti, & Sanz-Vergel, 2014), such as the career aspect and in the psychological field (Sonnentag, 2003; Schaufeli, Shimazu, Hakanen, Salanova, & De Witte, 2018),

764 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Figure 2: Research model.

our dependent variable is work engagement behavior, which refers to physical engagement.

External interventions, such as monetary rewards, can be seen as an important determinant factor for employee motivation and performance, which will lead to returns in terms of firm-level performance (Aguinis, Joo, & Gottfredson, 2013). However, external interventions, monetary or nonmonetary, may crowd out or crowd in intrinsic motivation. Current research is adopting two basic psychological processes to examine the crowding-out effect of external interventions on intrinsic motivation (Frey & Jegen, 2001). During the first psychological process, when external interventions are perceived to reduce the self-determination of individuals, extrinsic control replaces intrinsic motivation. During the second psychological process, when individuals feel that their involvement and competence are not appreciated, which means their own interest and involvement are reduced, they will decrease their effort in the activity. Yet external interventions may also crowd in intrinsic motivation if they perceive the interventions to be supportive (Osterloh & Frey, 2000), which means that self-esteem and self-determination are not damaged by external interventions. Monetary incentives seem to be an important way to improve intrinsic motivators without losing freedom. For Internet taxi drivers, monetary rewards may damage the intrinsic motivator if the drivers feel they are being controlled by the external interventions of the organizations. However, the monetary rewards could improve the drivers’ intrinsic motivators if they perceive that the external interventions are supportive measures of their work. Monetary rewards could thus be a positive intrinsic motivator because they help meet the

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drivers’ biological and physiological needs as well as some higher-level needs (e.g., safety needs, esteem needs, and self-actualization needs) (Maslow, 1954; Aguinis et al., 2013). In the context of the IT-enabled sharing economy, the following hypothesis is developed:

H1: Monetary rewards relate positively to Internet taxi drivers’ intrinsic motivators in the context of the IT-enabled sharing economy.

Jurkiewicz and Giacalone (2004) established a positive relationship between workplace spirituality and employee motivation. The three components of work- place spirituality (i.e., the realization of a deeper sense and meaning, a closer relationship with colleagues, and an alignment of organizational values) benefit employees and organizations. Spiritual employees’ behavior may lead to increased job satisfaction and further affect intrinsic motivation (Gotsis & Kortezi, 2008). Fostering workplace spirituality helps individuals to feel connections with them- selves, the community, and the organization (Guillén, Ferrero, & Hoffman, 2015) and be motivated intrinsically (Jurkiewicz & Giacalone, 2004). Both organization- level workplace spirituality and personal-level workplace spirituality were found to relate positively to intrinsic motivation (Kolodinsky et al., 2008). Internet taxi drivers can use mobile apps to share information about their personal feelings sur- rounding their work, community and taxi platforms. Good outcomes from those levels of workplace spirituality could have a positive influence on the intrinsic motivators of Internet taxi drivers. Based on abovementioned works, the following hypothesis is developed:

H2: Workplace spirituality relates positively to Internet taxi drivers’ intrinsic motivators in the context of the IT-enabled sharing economy.

Motivation is a fundamental component of almost all research models re- garding human performance (Pinder, 2011; Cerasoli et al., 2014) because it can explain why one kind of specific or usual behavior happens, changes, or disap- pears. Much of the previous research examining the interrelationship of intrinsic motivation, extrinsic incentives, and performance has focused on intrinsic motiva- tion as a predictor of performance. Employee engagement relates to employees’ emotions in the environment (Roof, 2015). When people perceive that their work fits their expectations, they support each other in work, seek greater quality in their job, and engage more in their work (Pawar, 2009). Previous research has found a positive connection between intrinsic motivation and employee engagement for the creative process (Zhang & Bartol, 2010). Engaged employees who work for fun and enjoy their job are intrinsically motivated (Schaufeli, 2013). Thus, it is ben- eficial to improve the Internet taxi drivers’ work engagement by motivating them intrinsically because intrinsic motivators would encourage them to work harder and engage more in the work. Therefore, the following hypothesis is presented:

H3: Intrinsic motivators relate positively to Internet taxi drivers’ work en- gagement in the context of the IT-enabled sharing economy.

(2) Measurement of variables

We used existing scales from previous research. In conclusion, there are eight reflective constructs: monetary rewards, meaningful work, sense of commu- nity, alignment of values, stress reduction, self-efficacy, job autonomy, and work engagement.

766 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Table 3: Demographic distribution of the survey respondents.

Items Category Frequency Ratio

Gender Male 175 74.5% Female 60 25.5%

Age (years) <25 19 8.1% 25–34 158 67.2% 35–44 51 21.7% �45 7 3.0%

Length of driving a traditional taxi Never 66 28.1% <1 year 14 6.0%

1–5 years 106 45.1% 5–10 years 44 18.7% >10 years 5 2.1%

Length of driving an Internet taxi <3 months 6 2.6% 3–6 months 45 19.1%

6 months to 1 year 77 32.8% >1 year 107 45.5%

The interviews conducted with 35 Internet taxi drivers revealed three intrinsic motivators: stress reduction, job autonomy, and self-efficacy. We assessed stress reduction by adapting five items from the measurements used by Hennessy and Wiesenthal (1997); job autonomy using four items from the measurements used by Ahuja, Chudoba, Kacmar, McKnight, and George (2007); and self-efficacy using four measures adopted from Jones (1986). Workplace spirituality, which was assessed using the scale developed by Milliman et al. (2003), was grouped into three subscales that reflect its underlying dimensions: meaningful work (four items), sense of community (four items), and alignment of values (four items). In our research, we refer to work engagement as physical engagement, which was assessed using six items (Rich et al., 2010). As no previous measure had been developed for measuring monetary rewards available for our research, we developed four items. All items were measured on a seven-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Eight items were discarded because they contributed significantly to the low reliability. As presented in Table A1 in the Appendix, the final questionnaire consisted of 27 items.

(3) Study design, procedure, and participants

The data were collected through a survey administered to Internet taxi drivers in China in 2017. A power analysis using G*power 3.1 computer software (Faul, Erdfelder, Lang, & Buchner, 2007) was conducted to calculate a suitable sample size. The results indicated that a sample size of 53 would be sufficient using a one- tailed test and a power (1 – β) = .95, given α = .05. We asked the interviewees to distribute questionnaires to their colleagues through WeChat groups. The survey invitation was sent to 500 Internet taxi drivers, and 333 subjects responded to the survey request, resulting in a survey response rate of 66.6%. We received 235 usable responses (175 males and 60 females). As presented in Table 3, the majority of the respondents were aged 25–34 years old, and their average experience of driving

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a traditional taxi ranged from 1 to 5 years. In addition, 45.5% of the respondents that gave usable responses had worked as Internet taxi drivers for more than a year.

DATA ANALYSIS AND RESULTS

We selected partial least squares structural equation modeling (PLS-SEM) to test the quality of the measurement models and the research hypotheses. This method is based on an iterative method that maximizes the explained variance of endogenous constructs (Fornell & Bookstein, 1982). In addition, the ability of partial least squares structural equation modeling to handle problematic modeling issues such as unusual data characteristics and highly complex models is convincing in social sciences (Hair, Sarstedt, Hopkins, & Kuppelwieser, 2014). To analyze the data, we selected SmartPLS 3.2.7 and Advanced Analysis of Composites (ADANCO) 2.0.1 to test the research hypotheses and the research model. The following subsections first assess the reliability and validity of the measurement model, and then present the results of the hypothesis testing of latent variables.

Assessment of Construct Measurements

Because all our latent constructs are reflective, we implemented the evaluation of reflective measurement based on their internal consistency reliability, convergent validity, and discriminant validity. Internal consistency reliability is used to mea- sure the consistency of different items in the same construct. Because in PLS-SEM, the composite reliability (CR) is considered a more suitable criterion of reliabil- ity than Cronbach’s α (Hair, Hult, Ringle, & Sarstedt, 2016), we used composite reliability to measure the internal consistency reliability. As presented in Table 4, the composite reliability values in this research are between 0.8 and 0.9, which can be regarded as satisfactory. Convergent validity is the extent of the positive relation between a measure and alternative measures of the same construct (Hair et al., 2016). The average variance extracted (AVE) of all constructs above 0.5 and almost all outer loadings of the indicators above 0.7 provides evidence that a specific construct converges or shares a high proportion of variance. Because the removal of indicators with outer loadings between 0.4 and 0.7 cannot lead to an in- crease in the composite reliability, these indicators are not deleted in this research. Variance inflation factor (VIF) values can be used to evaluate multicollinearity (Benitez, Henseler, & Castillo, 2017). All VIF values ranged from 1.176 to 2.096, suggesting that multicollinearity is not a problem in our data.

Discriminant validity refers to the extent to which a construct is truly distinct from others by empirical standards (Hair et al., 2016). Tables 5–7 present the discriminant validity evaluations based on the Fornell–Larcker criterion, cross-loading, and the heterotrait–monotrait ratio of correlations (HTMT). Table 5 shows that the square root of each construct’s variance inflation factor is greater than its highest correlation with any other construct, and Table 6 shows that every indicator loading of eight reflective constructs has a greater correlation with its

768 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Table 4: Results of EFA and CFA.

Constructs Items VIF Weight Factor

Loadings

Composite Reliability

(CR)

Average Variance Extracted

(AVE)

Meaningful work MW1 1.509 0.332*** 0.771*** 0.877 0.590 MW2 1.383 0.380*** 0.772***

MW3 1.472 0.295*** 0.747***

MW4 1.611 0.296*** 0.779***

Sense of community SC1 1.319 0.363*** 0.729*** 0.848 0.576 SC2 1.646 0.329*** 0.795***

SC3 1.438 0.299*** 0.726***

SC4 1.692 0.327*** 0.786***

Alignment of values AL1 2.096 0.404*** 0.853*** 0.861 0.705 AL2 1.380 0.491*** 0.832***

AL3 2.093 0.301*** 0.822***

Monetary rewards MR1 1.558 0.376*** 0.665*** 0.852 0.674 MR2 1.575 0.452*** 0.799***

MR3 1.487 0.387*** 0.686***

Stress reduction SR1 1.176 0.432*** 0.722*** 0.874 0.777 SR2 1.593 0.533*** 0.867***

SR3 1.518 0.304* 0.743***

Job autonomy JA1 1.479 0.495*** 0.839*** 0.845 0.650 JA2 1.709 0.362*** 0.831***

JA3 1.364 0.380*** 0.747***

Self-efficacy SE1 1.371 0.427*** 0.794*** 0.819 0.602 SE2 1.413 0.399*** 0.791***

SE3 1.332 0.438*** 0.790***

Physical engagement PE1 1.389 0.386*** 0.778*** 0.874 0.546 PE2 1.196 0.288*** 0.628***

PE3 1.514 0.306*** 0.746***

PE4 1.602 0.363*** 0.800***

*p < .05, ***p < .001, one-tailed test.

Table 5: Mean, SD, and discriminant validity evaluation based on the Fornell– Larcker criterion.

Construct Mean SD 1 2 3 4 5 6 7 8

1. Monetary rewards 5.565 1.128 0.517 2. Physical

engagement 5.450 1.210 0.354 0.549

3. Meaningful work 6.238 0.923 0.253 0.377 0.589 4. Sense of

community 5.790 1.026 0.165 0.338 0.498 0.577

5. Alignment of values

6.039 0.916 0.085 0.167 0.408 0.448 0.699

6. Stress reduction 5.685 1.057 0.034 0.036 0.038 0.054 0.033 0.609 7. Self-efficacy 6.115 0.904 0.238 0.345 0.175 0.149 0.103 0.047 0.627 8. Job autonomy 4.851 1.595 0.139 0.109 0.139 0.131 0.089 0.027 0.101 0.651

All bold values are significant with p < .001.

Hua et al. 769

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770 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Table 7: Discriminant validity based on the heterotrait–monotrait ratio of corre- lations (HTMT).

Construct 1 2 3 4 5 6 7 8

1. Stress reduction 2. Job autonomy 0.239 3. Self-efficacy 0.296 0.439 4. Monetary rewards 0.239 0.423 0.581 5. Sense of community 0.316 0.511 0.531 0.517 6. Meaningful work 0.247 0.488 0.562 0.565 0.951 7. Alignment of values 0.219 0.372 0.425 0.302 0.888 0.813 8. Physical engagement 0.245 0.439 0.807 0.699 0.811 0.814 0.516

constructs than with other constructs (Benitez et al., 2017), thus confirming the discriminant validity.

Common Method Variance (CMV)

Common method variance (CMV), a main source of measurement error, is a po- tential problem in research on behavior because it threatens the validity of the data analysis and the relationships between measures (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). We used two general ways to control method bias in this research that related to the design of the study’s procedures and statistical controls. First, during the design of the study’s procedures, we attempted to minimize method bias by protecting respondent anonymity and reducing evaluation apprehension: we informed all respondents that their answers would be anonymous and that there were no right or wrong answers. We also attempted to control method bias by improving the scale items: we avoided using ambiguous or unfamiliar terms, double-barreled questions, and complicated syntax, and we kept the questions simple, specific, and concise (Podsakoff et al., 2003). Second, we applied the PLS marker variable approach following the procedures suggested by Rönkkö and Ylitalo (2011). We identified marker variables (monetary punishment) in the same survey of our research, but these were not included in the research model being tested. We then added marker indicators as an exogenous variable to predict each endogenous construct in the research model, and finally, we compared the model with and without marker variables. Table 8 shows that no significant correlations between the marker variable and other constructs of interest were found in this study, and the significant paths in the baseline model remained significant after adding the marker variable; thus, common method bias is not a cause for concern.

Structural Model and Hypothesis Testing

As presented in Table 9, the standardized root mean squared residual (SRMR), the unweighted least squares discrepancy (dULS), and the geodesic discrepancy (dG) were examined to evaluate the discrepancy between the empirical correlation matrix and the model-implied correlation matrix, and indicate the goodness of

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Table 8: Common method bias assessment.

Relationships

Research Model (without Marker

Variable)

Research Model (with Marker

Variable)

Monetary rewards→Intrinsic motivators 0.384*** 0.384*** Workplace spirituality→Intrinsic motivators 0.319*** 0.319*** Intrinsic motivators→Work engagement 0.609*** 0.606*** Marker→Intrinsic motivators –0.001 Marker→Work engagement –0.055 ***p < .001.

Table 9: Estimated model fit evaluation.

Discrepancy Value HI95 HI99 Conclusion

SRMR 0.060 0.057 0.063 Supported dULS 0.331 0.299 0.355 Supported dG 0.123 0.117 0.134 Supported

the estimated model (Henseler et al., 2014; Henseler, 2017). The lower the values of the SRMR, dULS, and dG, the better the fit of the theoretical model (Henseler, 2017; Benitez, Llorens, & Braojos, 2018). The ADANCO 2.0.1 provided the 95% percentile (“HI95”) and the 99% percentile (“HI99”) values for the SRMR, dULS, and dG (Table 9). Thus, if the SRMR, dULS, and dG exceed these values, the model may not be true (Henseler, 2017). The current model in our research demonstrated an acceptable-to-good fit.

As shown in Figure 3, monetary rewards and workplace spirituality explained 37% of the variance in intrinsic motivators and 37.1% of the variance in work en- gagement, which indicate that monetary rewards and workplace spirituality relate positively to intrinsic motivation, thus supporting H1 and H2. In addition, intrinsic motivators were found to relate positively to work engagement, thus supporting H3. The findings also showed that monetary incentives crowd in intrinsic motivators for Internet taxi drivers.

We provided the values of the path coefficients, their significance level, and Cohen’s f2 to measure the explanatory power of our research model. As shown in Table 10 and Figure 3, the relationship between monetary rewards and intrinsic motivators and the relationship between intrinsic motivators and work engagement are significant. Intrinsic motivators mediated the effect of monetary rewards on work engagement and the effect of workplace spirituality on work engagement. The total effect of monetary rewards on intrinsic motivators is 0.384, with Cohen’s f2 = 0.178. The total effect of workplace spirituality on intrinsic motivators is 0.319, with Cohen’s f2 = 0.123. The total effect of intrinsic motivators on work engagement is 0.609, with Cohen’s f2 = 0.589. According to Cohen’s (1988) guidelines, Cohen’s f2 �0.02, �0.15, and �0.25 are taken as small, medium, and large effect sizes. Cohen’s f2 values for the hypothesized relationships included in our study ranged from 0.123 to 0.589 (small to large).

772 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Figure 3: Hypotheses testing results. ***denotes significance at the .001 level; ** denotes significance at the .01 level.

Table 10: Total effects overview.

Effect Beta Indirect Effects

p-Value (2-Sided)

p-Value (1-Sided)

Total Effect

Cohen’s f2

Monetary rewards→intrinsic motivators

0.384 .000 .000 0.384 0.178

Monetary rewards→work engagement

0.234 .000 .000 .234

Intrinsic motivators→work engagement

0.609 .000 .000 0.609 0.589

Workplace spirituality→intrinsic motivators

0.319 .000 .000 0.319 0.123

Workplace spirituality→work engagement

0.194 .001 .001 0.194

Post Hoc Analysis

Post hoc analysis tests were conducted to evaluate whether a direct relationship ex- ists between monetary rewards and work engagement and between workplace spir- ituality and work engagement. As presented in Figure 4, the relationship between monetary rewards and work engagement and the relationship between workplace spirituality and work engagement proved to be significant and positive. Monetary rewards were found to relate positively to work engagement with a coefficient of

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Figure 4: Post hoc analysis. ***denotes significance at the .001 level; **denotes significance at the .01 level.

Table 11: Summary of mediation testing results.

Mediation Test (ab) Full/Partial Mediation Test (c′)

Variable Independent Variable

Mediating Variable

2.5% Lower bound

97.5% Upper bound

Zero included?

2.5% Lower bound

97.5% Upper bound

Zero included?

Type of mediation

Monetary rewards

Intrinsic motivators

0.037 0.179 No 0.080 0.437 No Partial

Workplace spirituality

Intrinsic motivators

0.021 0.165 No 0.266 0.517 No Partial

0.259, and workplace spirituality was found to relate positively to work engage- ment with a coefficient of 0.384.

We also conducted a mediation analysis following the procedures suggested in previous studies (Shrout & Bolger, 2002; Vance, Lowry, & Eggett, 2015). As presented in Table 11, we obtained 5,000 resamples and conducted the 95% bootstrap percentile intervals for both indirect and direct effects and the results of the mediation testing. The effects of monetary rewards and workplace spirituality on work engagement are both partially mediated by intrinsic motivators.

Summary of Findings

The findings from both studies answered our research questions. In response to the first research question (i.e., what intrinsic motivators of Internet taxi drivers

774 Monetary Rewards, Intrinsic Motivators, and Work Engagement

influence their work engagement), the results showed that stress reduction, job autonomy, and self-efficacy are three important dimensions that motivate Internet taxi drivers intrinsically, which supported findings from previous studies (O’Neill & Davis, 2011; Skaalvik & Skaalvik, 2016). In response to the second question, the statistical results of structural equation modeling and hypothesis testing showed that those who received positive monetary incentives were motivated intrinsically and showed a desire to engage more in their work, which verified the crowding-in effect of extrinsic incentives.

The findings highlighted the important role of workplace spirituality and monetary rewards in the IT-enabled sharing economy. The analysis of a base- line model and the post hoc analysis showed that workplace spirituality relates positively to intrinsic motivators and work engagement. In addition, monetary rewards relate positively to intrinsic motivators and work engagement. Both mon- etary rewards and workplace spirituality could improve work engagement through an intrinsic motivator. This finding extended motivation crowding theory by con- sidering aspects of the employees’ external environments other than monetary incentives. Thus, monetary rewards and workplace spirituality both play pivotal roles in determining intrinsic motivators. Another important finding was that in- trinsic motivators relate positively and significantly to work engagement. Thus, intrinsic motivators, monetary rewards, and workplace spirituality are important determinants of work engagement.

IMPLICATIONS AND CONCLUSION

Although our findings verify the crowding-in effect of monetary rewards on in- trinsic motivators, the crowding-out effect is not verified. A possible explanation for this is that the activities of engaging in car-sharing services cannot provide Internet taxi drivers with inherent rewards. Thus, external rewards are supportive measures that stimulate their behavior. Another possible explanation is that the tangible rewards related with the task and work are seen as a part of the work itself. Therefore, Internet taxi drivers are willing to engage more in work.

Theoretical Contribution

One primary theoretical contribution of this study is that it explored the mediating role of intrinsic motivators in the context of the IT-enabled sharing economy for Internet taxi drivers. We found that intrinsic motivators have a mediating effect on monetary rewards and work engagement. The findings suggest that it is useful to apply external interventions to stimulate Internet taxi drivers’ work engagement. Whereas most studies in the fields of economics and operations management have examined the effects of economic incentives on intrinsic motivation and performance or employee behavior (Gneezy et al., 2011; Dierynck et al., 2012; Ederer & Manso, 2013), this study emphasizes the positive effects of monetary incentives on intrinsic motivators and work engagement. This study sheds new light on the positive effects of monetary rewards on the intrinsic motivators and work engagement of Internet taxi drivers.

Hua et al. 775

The second contribution of this study is that it extends motivation crowding theory to a new research field (i.e., the IT-enabled sharing economy) by shedding light on work engagement and workplace spirituality. Although previous research has examined the relationship between monetary rewards and intrinsic motivation and focused on the fields of psychology (Wiersma, 1992; Cerasoli et al., 2014) and behavior (Lin, 2007), this study identified three intrinsic motivators for Internet taxi drivers in the context of the IT-enabled sharing economy: stress reduction, job autonomy, and self-efficacy. Therefore, this study extends the explanation of motivation crowding theory to include employee behavior in the IT-enabled sharing economy.

Third, this work contributes to existing knowledge by providing a new per- spective on investigating work engagement in the context of the IT-enabled sharing economy. Although a large and growing body of literature has investigated work engagement, it has mostly focused on the psychological state of engagement (Kahn, 1990; Schaufeli et al., 2002; Schaufeli et al., 2018). By contrast, this study focused on the behavioral aspect of work engagement, measured through the physical en- gagement items in the IS-related field. The empirical findings in this study provide a new understanding of employee performance from the perspective of work engage- ment, especially physical engagement in our specific context. Thus, researchers can measure employee performance and behavior by improving work engagement.

Fourth, we have extended the previous research associated with workplace spirituality (Cavanagh & Bandsuch, 2002; Gotsis & Kortezi, 2008) to include the IT-enabled sharing economy in terms of Internet taxi drivers’ behavior. We have identified the importance of workplace spirituality in the context of the IT- enabled sharing economy, in terms of improving work recognition and working relationships, and aligning organizational values. Confirming the correlation paths among workplace spirituality, intrinsic motivators and work engagement implies that workplace spirituality is an important determinant factor of work engage- ment because it meets the need for Internet taxi drivers to work in a much better environment in the context of the IT-enabled sharing economy.

Last, this work contributes to the existing knowledge of operations man- agement from the perspective of labor intensity and trade-off between inputs and outputs. Compared with previous studies (Sawhney, 2013; Netland, Schloetzer, & Ferdows, 2015), which explored the relationship between labor flexibility and plant performance and the negative experiences of financial incentives, this research emphasizes that the trade-off between inputs and outputs and the conversion of monetary rewards and labor inputs into work engagement should be considered in the design of business strategies and operations. The findings indicate that in- trinsic motivators and monetary rewards are important determinants of Internet taxi drivers’ work engagement. As a vital intrinsic motivator, stress reduction has shown its influence in determining employee behavior. Thus, organizations should consider the connection between labor intensity and service quality when designing and controlling the production process.

776 Monetary Rewards, Intrinsic Motivators, and Work Engagement

Practical Implications

This research has a number of important implications for managers of Internet taxi companies. Greater efforts are needed to ensure the effective management of Internet taxi drivers, the formulation of a corporate strategy, the improvement of an assessment system, the design of incentive systems, and appropriate humanistic care. Our findings suggest that monetary rewards and intrinsic motivators have significant effects on Internet taxi drivers’ work engagement in the IT-enabled sharing economy. Therefore, managers should provide extrinsic rewards in the form of money directly or indirectly to a certain degree. Equal institution in basic wage and performance-related pay could be considered for improving employee engagement. Similarly, management should enhance Internet taxi drivers’ self- efficacy by providing training to improve their driving skills and facilitate their use of smart phones and car-hailing apps.

Another important practical implication is that the findings suggest several implications for developers of car-hailing apps. A reasonable approach to tackle this issue could be to maintain reduced stress levels, control the length of work time, and improve job autonomy by giving more freedom to drivers during work time. Meanwhile, a number of important changes, such as improving the car- hailing apps to facilitate the communication convenience among Internet taxi drivers, need to be made to improve workplace spirituality. In addition, lectures on spirituality (Gupta, Kumar, & Singh, 2014), sports events among all employees, and regular training could be helpful in improving Internet taxi drivers’ work engagement. Some measures could also be useful during the software development stage to strength the connections between colleagues and meaningfulness of work by humanized design.

This research also has significant implications for the decision-making of policymakers from the government or organizations. By understanding the business model, the future directions of Internet taxis, and the work conditions of Internet taxi drivers, policymakers can formulate policies that correspond to the actual situation. Overall, this study has important implications for developing effective management measures for policymakers to motivate Internet taxi drivers to engage more in work. Because more and more people are engaging in the IT-enabled sharing economy and car-sharing services, a reasonable policy is essential to coordinate relations between Internet taxi companies and Internet taxi drivers, improve the drivers’ work motivation and maintain reduced stress levels. On the one hand, this study could encourage the development of Internet taxis, improve the service performance, and provide more convenient transportation to citizens. On the other hand, it helps to protect the health and safety of the Internet taxi drivers.

Limitations and Future Research

This study has some limitations. First, this study did not include all behavioral aspects of the employees. This study is also limited by its focus on physical engagement and the lack of a control variable that affects work engagement. Future studies could test the effects of intrinsic motivators and monetary incentives from other aspects, such as the relationship between monetary punishment and intrinsic motivators. Like most research studies related to motivation crowding

Hua et al. 777

theory, the study is limited by its focus on positive monetary incentives, ignoring negative monetary incentives, which future studies could investigate. Furthermore, the effect of external incentives, except for monetary incentives, on employee behavior should be considered in future research. Although previous studies have suggested that the extent of monetary incentives affected the outcome of behavior (Bartol & Srivastava, 2002; Rode et al., 2015), it was difficult to test the effects in this study. Future studies could therefore conduct a longitudinal study to investigate how to control monetary rewards and monetary punishments to maximize company interests and reach a higher level of employee satisfaction and psychological engagement. In addition, a greater focus on trust between Internet taxi drivers and passengers could produce interesting findings that account more for relationship building in the context of the IT-enabled sharing economy.

CONCLUSION

In conclusion, this research builds on motivation crowding theory by establishing the role of workplace spirituality in the IT-enabled sharing economy context. Apart from the crowding-in effect of monetary rewards on intrinsic motivation and work engagement, the interaction between workplace spirituality and intrinsic motivators has been discussed as an important determinant of work engagement. Additionally, the intrinsic motivators were divided into three dimensions: stress reduction, job autonomy, and self-efficacy. The findings showed that work engagement can be improved by providing monetary rewards and improving work engagement, which included increased meaningfulness of work, improved working relationships, and an improved alignment of values between organizations and employees. This finding underscores the importance of the work environment and an incentive system. This research serves as a basis for future studies on work engagement in the emerging research field of the IT-enabled sharing economy. Future research should expand our model by identifying other types of employee behavior and performance, such as those based on ratings from passengers and evaluations from superiors.

SUPPORTING INFORMATION

Additional supporting information may be found online in the Supporting Infor- mation section at the end of the article.

APPENDIX

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784 Monetary Rewards, Intrinsic Motivators, and Work Engagement

APPENDIX

Table A1: Measurement items.

Construct Item Code

Questions and Item Scales (1 = Strongly Disagree to 7 = Strongly Agree)

Stress reduction SR1 I am not concerned about getting to my destination on time.

SR2 I am not annoyed if I am driving behind other vehicles.

SR3 I do not mind being overtaken. Job autonomy JA1 I control the content of my job.

JA2 I have a lot of freedom to decide how I perform assigned tasks.

JA3 I have the authority to initiate projects at my job. Self-efficacy SE1 My job is well within the scope of my abilities.

SE2 I feel I am overqualified for the job I am doing. SE3 I have all the technical knowledge I need to deal with

my job, all I need now is practical experience. Physical engagement PE1 I exert my full effort to my job.

PE2 I devote a lot of energy to my job. PE3 I try my hardest to perform well on my job. PE4 I strive as hard as I can to complete my job.

Meaningful work MW1 My spirit is energized by work. MW2 My work is connected to what I think is important in

life. MW3 I see a connection between my work and the social

good. MW4 I understand what gives my work personal meaning.

Sense of community SC1 Working cooperatively with others is valued. SC2 I feel part of a community. SC3 I believe employees genuinely care about each other. SC4 I feel there is a sense of being a part of a family.

Alignment of values AL1 The organization cares about all its employees. AL2 I feel connected with the organization’s goals. AL3 The organization is concerned about the health of

employees. Monetary rewards MR1 The oil card provided by the organization inspires me.

MR2 The material benefits from organizations during holidays inspire me.

MR3 I am happy if I get bonus after receiving credit from passengers.

Hua et al. 785

Ying Hua is a professor of information system and associate dean in the School of Information Technology and Management in the University of International Business and Economics, Beijing, China.

Xusen Cheng is a professor of information system in the School of Informa- tion Technology and Management in the University of International Business and Economics, Beijing, China.

Tingting Hou is a PhD candidate in the School of Information Technology and Management in the University of International Business and Economics, Beijing, China.

Rob Luo is a visiting professor in the School of Information Technology and Management in the University of International Business and Economics, Beijing, China.