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Norman Au

Bio: Norman Au is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Hospitality industry & Tourism. The author has an hindex of 20, co-authored 52 publications receiving 3069 citations. Previous affiliations of Norman Au include Mahidol University International College.


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TL;DR: The authors applied the component-based structural equation modeling technique of partial least squares to examine online travelers' perceptions of the credibility of UGC sources and how these perceptions influence attitudes and intentions toward UGC utilization in the travel planning process.
Abstract: Recent press reports and complaints by hoteliers have called into question the credibility of travel-related user-generated content (UGC). Yet our understanding of the role of credibility perceptions in the context of UGC is limited, notwithstanding the rising interest in social media. Using an online survey of 661 travel consumers, this study applies the component-based structural equation modeling technique of partial least squares to examine online travelers’ perceptions of the credibility of UGC sources and how these perceptions influence attitudes and intentions toward UGC utilization in the travel planning process. The model also draws on the theory of homophily to make predictions about the antecedent of credibility. Results validate the Source Credibility Theory in the context of UGC but also accentuate the central mediating role of attitude. In addition, the study finds support for perceptual homophily as a critical determinant of both credibility and attitude. Theoretical and managerial implicat...

594 citations

Journal ArticleDOI
TL;DR: In this paper, the intention to use consumer-generated media for travel planning by introducing new factors into the conventional TAM and using a partial least squares' estimation was investigated using an online survey of travel consumers.

412 citations

Journal ArticleDOI
TL;DR: The conclusion is that merely focusing on the technical soundness of the IS and the way in which it benefits employees may not be sufficient, rather, the input requirements of users for achieving the corresponding needs fulfillments also need to be examined.
Abstract: End user satisfaction (EUS) is critical to successful information systems implementation. Many EUS studies in the past have attempted to identify the antecedents of EUS, yet most of the relationships found have been criticized for their lack of a strong theoretical underpinning. Today it is generally understood that IS failure is due to psychological and organizational issues rather than technological issues, hence individual differences must be addressed. This study proposes a new model with an objective to extend our understanding of the antecedents of EUS by incorporating three well-founded theories of motivation, namely expectation theory, needs theory, and equity theory. The uniqueness of the model not only recognizes the three different needs (i.e., work performance, relatedness, and self-development) that users may have with IS use, but also the corresponding inputs required from each individual to achieve those needs fulfillments, which have been ignored in most previous studies. This input/needs fulfillment ratio, referred to as equitable needs fulfillment, is likely to vary from one individual to another and satisfaction will only result in a user if the needs being fulfilled are perceived as "worthy" to obtain. The partial least squares (PLS) method of structural equation modeling was used to analyze 922 survey returns collected form the hotel and airline sectors. The results of the study show that IS end users do have different needs. Equitable work performance fulfillment and equitable relatedness fulfillment play a significant role in affecting the satisfaction of end users. The results also indicate that the impact of perceived IS performance expectations on EUS is not as significant as most previous studies have suggested. The conclusion is that merely focusing on the technical soundness of the IS and the way in which it benefits employees may not be sufficient. Rather, the input requirements of users for achieving the corresponding needs fulfillments also need to be examined.

353 citations

Journal ArticleDOI
TL;DR: Experimental results showed that using the neural network model to forecast Japanese arrivals outperforms multiple regression, naive, moving average, and exponent smoothing.

307 citations

Journal ArticleDOI
TL;DR: In this paper, the authors explore consumer reviews with robotics based on the five dimensions for evaluating user experiences (i.e. embodiment, emotion, human-oriented perception, feeling of security and co-experience), as derived from research in human-robot interactions (HRI).
Abstract: The purpose of this study is to explore consumer reviews with robotics based on the five dimensions for evaluating user experiences (i.e. embodiment, emotion, human-oriented perception, feeling of security and co-experience), as derived from research in human-robot interactions (HRI).,The study first reviews the five dimensions for evaluating user experiences in HRI and then analyzes user experiences with robotics at four hotels (i.e. Yotel New York, Aloft Cupertino, Henn-na Hotel Japan and Marriott Residence Inn LAX) based on reviews on TripAdvisor, Agoda, Yelp and Booking.com.,The findings highlight the influence of robotic embodiment and human-oriented perceptions on consumer experiences. The findings also suggest that users and robots can co-create novel experiences, with some guests even proactively seeking new opportunities to interact and communicate with robots to develop a certain level of “relationship” with them.,An understanding of user experiences from HRIs can inform future hospitality and tourism research and management.,This study contributes to hospitality and tourism management by highlighting current practices with robotics to suggest areas of improvements for enhancing future consumer experiences.,Consumer experiences will change rapidly as hospitality and tourism management deploys robotics in the future.,This is one of the early studies in the field to explore consumer experiences with robotics based on the five dimensions for evaluating user experiences from research in HRI. In doing so, this study provides a number of theoretical and managerial implications relevant for hospitality and tourism research and practice.

245 citations


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TL;DR: Gefen et al. as mentioned in this paper presented a comprehensive, organized, and contemporary summary of the minimum reporting requirements for structural equation modeling (PLS-SEM) applications.
Abstract: Wold’s (1974; 1982) partial least squares structural equation modeling (PLS-SEM) ap-proach and the advanced PLS-SEM algorithms by Lohmoller (Lohmoller 1989) have enjoyed steady popularity as a key multivariate analysis methods in management infor-mation systems (MIS) research (Gefen et al. 2011). Chin’s (1998b) scholarly work and technology acceptance model (TAM) applications (e.g., Gefen and Straub 1997) are milestones that helped to reify PLS-SEM in MIS research. In light of the proliferation of SEM techniques, Gefen et al. (2011), updating Gefen et al. (2000), presented a compre-hensive, organized, and contemporary summary of the minimum reporting requirements for SEM applications. Such guidelines are of crucial importance for advancing research for several reasons. First, researchers wishing to apply findings from prior studies or wanting to contribute to original research must comprehend other researchers’ decisions in order to under-stand the robustness of their findings. Likewise, when studies arrive at significantly different results, the natural course is to attempt explaining the differences in terms of the theory or concept employed, the empirical data used, and how the research method was applied. A lack of clarity on these issues, including the methodological applications, contradicts the goals of such studies (Jackson et al. 2009). Even worse, the misapplication of a technique may result in misinterpretations of empirical outcomes and, hence, false conclusions. Against this background, rigorous research has a long-standing tradition of critically reviewing prior practices of reporting standards and research method use (e.g., Boudreau et al. 2001). While the use of covariance-based SEM (CB-SEM) techniques has been well documented across disciplines (e.g., Medsker et al. 1994; Shook et al. 2004; Steenkamp and Baumgartner 2000), few reviews to date have investigated usage practices specific to PLS-SEM (see, however, Gefen et al. 2000). Previous reviews of such research practices were restricted to strategic management (Hulland 1999) and, more recently, marketing (Hair et al. 2012; Henseler et al. 2009), and accounting (Lee et al. 2011). The question arises as to how authors publishing in top IS journals such as MIS Quarterly have used PLS-SEM thus far, given the SEM recommendations of Gefen et al. (2011). By relating Gefen et al.’s (2011) reporting guidelines to actual practice, we attempt to identify potential problematic areas in PLS-SEM use, problems which may explain some of the criticism of how it has been applied (e.g., Marcoulides et al. 2009; Marcoulides and Saunders 2006). By reviewing previous PLS-SEM research in MIS Quarterly, we can hopefully increase awareness of established reporting standards. The results allow researchers to further improve the already good reporting practices that have been established in MIS Quarterly and other top journals and thus could become blueprints for conducting PLS-SEM analysis in other disciplines such as strategic management and marketing.

1,835 citations

Journal ArticleDOI
TL;DR: This work builds on the prior research related to IS success by summarizing the measures applied to the evaluation of IS success and by examining the relationships that comprise the D&M IS success model in both individual and organizational contexts.
Abstract: Since DeLone and McLean (D&M) developed their model of IS success, there has been much research on the topic of success as well as extensions and tests of their model. Using the technique of a qualitative literature review, this research reviews 180 papers found in the academic literature for the period 1992–2007 dealing with some aspect of IS success. Using the six dimensions of the D&M model – system quality, information quality, service quality, use, user satisfaction, and net benefits – 90 empirical studies were examined and the results summarized. Measures for the six success constructs are described and 15 pairwise associations between the success constructs are analyzed. This work builds on the prior research related to IS success by summarizing the measures applied to the evaluation of IS success and by examining the relationships that comprise the D&M IS success model in both individual and organizational contexts.

1,681 citations

Journal Article
TL;DR: This article provides a nontechnical overview of PLS and outline the ongoing discourses on SEM in general and on PLS in particular, and presents a basic framework for empirical research applying PLS as well as a detailed explanation of the different process steps.
Abstract: Empirical studies that use structural equation modeling (SEM) are widespread in information systems research. During the last few years, the component-based approach partial least squares (PLS) for testing structural models has become increasingly popular. At the same time, this approach's limitations have become a greater concern. Some researchers even suggest using alternative approaches that are considered superior to PLS. However, we believe that PLS is an adequate choice if the research problem meets certain characteristics and the technique is properly used. Thus, the intention of this article is to resolve potential uncertainties that researchers intending to use PLS might have. Consequently, we provide a nontechnical overview of PLS and outline the ongoing discourses on SEM in general and the PLS approach in particular. Furthermore, we present a basic framework for empirical research applying PLS as well as a detailed explanation of the different process steps. Finally, examples of information systems research using PLS are summarized to demonstrate its beneficial application and the appropriateness of the proposed framework. This article can serve as a helpful guide for inexperienced researchers applying PLS for the first time, but also as a reference guide for researchers with a better understanding of the field. Keywords: structural equation modeling, partial least squares, information systems research I. INTRODUCTION The information systems (IS) discipline examines socioeconomic systems that are characterized by the interplay between hardware and software on the one hand, as well as individuals, groups, and organizations on the other. For example, technology adoption, acceptance, and success, as well as the conditions under which these can be achieved are typical issues that are addressed by IS research. These research fields are similar in that their investigation requires the researcher to cope with constructs such as the beliefs, perceptions, motivation, attitude, or judgments of the individuals involved. These constructs are usually modeled as latent variables (LVs) that can be measured only through a set of indicators. Structural equation models describe the relationships between several of these LVs. A number of algorithms and software programs are available to estimate their relationships based on a dataset. Among these algorithms, the partial least squares (PLS) algorithm has become increasingly popular both in IS research and in other disciplines such as marketing (Albers 2010; Henseler et al. 2009) or strategic management (Hulland 1999). However, reminders of this approach's limitations have recently become more prominent. Consequently, researchers opt for a more careful application of PLS. Especially its statistical power at small sample sizes, the overall model fit, as well as the misspecification of measurement models have been the focus of recent discussions. To resolve the uncertainties that researchers intending to use PLS might have, we investigate current discourses on the PLS approach. In the following sections, we: * demonstrate the increasing popularity of PLS in the IS research community * outline the PLS approach by providing a nontechnical overview and reflecting on the ongoing discussion on structural equation modeling (SEM) in general and on PLS in particular * discuss differences between PLS and covariance-based approaches * present a basic framework for empirical research applying the PLS approach * provide examples of its beneficial application in IS research As a result, this paper helps SEM beginners and advanced researchers to make an informed decision about whether to use SEM or other alternative approaches to SEM. Even more, we present up-to-date recommendations on how to apply PLS appropriately. Section II demonstrates the increasing popularity of PLS for SEM in IS research by conducting a systematic review of literature that appeared in two prestigious IS journals during the last fifteen years. …

1,351 citations

03 Feb 2004
TL;DR: A review of the influence of group goals on group performance can be found in this article, where the authors discuss the role of cross-cognitive and affective factors in work motivation.
Abstract: Part One: Initial Considerations Chapter 1: Motivation in Organizations Mitchell, Terence R., and Daniels, Denise. Observation and Commentary on Recent Research in Work Motivation. Chapter 2: Conceptual Approaches to Motivation at Work Ryan, Richard M., and Deci, Edward L. 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1): 68-78. Mowday, Richard, and Colwell, Kenneth A. Employee reactions to unfair outcomes in the workplace: The contributions of Adams' equity theory to understanding work motivation. Cropanzano, Russell, and Rupp, Deborah. An overview of organizational justice: Implications for work motivation. Komaki, Judith. Reinforcement theory at work: Enhancing and explaining what employees do. Locke, Edwin A. 1996. Motivation through conscious goal setting. Applied and Preventive Psychology, 5: 117-124. Stajkovic, Alexander D., and Luthans, Fred. Social cognitive theory and self-efficacy: Implications for motivation theory and practice. Part Two: Central Issues in Motivation at Work Chapter 3: The Role of Cognitions, Beliefs, and Attitudes in Motivation Staw, Barry M. 1986. Organizational psychology and the pursuit of the happy/productive worker. California Management Review, 28(4): 40-53. Rousseau, Denise M., and Tijoriwala, Snehal A. 1999. What's a good reason to change? Motivated reasoning and social accounts in promoting organizational change. Journal of Applied Psychology, 84(4): 514-528. Luthans, Fred. Positive Organizational Behavior: Implications for Leadership and HR Development and Motivation. Chapter 4: The Role of Goals and Intentions in Motivation Klein, Howard J., Wesson, Michael J., Hollenbeck, John R., and Alge, Bradley J. 1999. Goal commitment and the goal-setting process: Conceptual clarification and empirical synthesis. Journal of Applied Psychology, 6: 885-896. O'Leary-Kelly, Anne M., Martocchio, Joseph J., and Frink, Dwight D. 1994. A review of the influence of group goals on group performance. Academy of Management Journal, 37(5): 1285-1301. Crown, Deborah F., and Rosse, Joseph G. 1995. Yours, mine, and ours: Facilitating group productivity through the integration of individual and group goals. Organizational Behavior and Human Decision Processes, 64(2): 138-150. Chapter 5: The Role of Affect in Motivation Raghunathan, Rajagopal, and Pham, Michel T. 1999. All negative moods are not equal: Motivational influences of anxiety and sadness on decision-making. Organizational Behavior and Human Decision Processes, 79(1): 56-77. Venkatesh, Viswanath, and Speier, Cheri. 1999. Computer technology training in the workplace: A longitudinal investigation of the effect of mood. Organizational Behavior and Human Decision Processes, 79(1): 1-28. Chapter 6: The Role of Social Influences in Motivation Porter, Lyman W., Lawler, Edward E. III, and Hackman, J. Richard. 1975. Ways groups influence individual effectiveness. (Holdover from previous edition) Vardi, Yoav and Wiener, Yoash. 1996. Misbehavior in organizations: A motivational framework. Organization Science, 7(2): 151-165. Whyte, Glen. 1998. Recasting Janis's groupthink model: The key role of collective efficacy in decision fiascoes. Organizational Behavior and Human Decision Processes, 73(2/3): 185-209. Chapter 7: The Role of Cross-Cultural Influences in Work Motivation Hofstede, G. 1993. Cultural constraints in management theories. Academy of Management Executive, 7(1): 81-94. Sanchez-Runde, Carlos J., and Steers, Richard M. Cultural influences on work motivation and performance. Frese, Michael, Kring, Wolfgang, Soos, Andrea, Zempel, Jeannette. 1996. Personal initiative at work: Differences between east and west Germany. Academy of Management Journal, 39(1): 37-63. Meek, Christopher B. 1999. Ganbatte: Understanding the Japanese employee. Business Horizons, January-February, 27-36. Chapter 8: The Role of Individual Differences in Motivation O'Reilly, Charles A. III and Chatman, Jennifer A. 1994. Working smarter and harder: A longitudinal study of managerial success. Administrative Science Quarterly, 39: 603-627. Pilegge, Anthony J. and Holtz, Rolf. 1997. The effects of social identity on the self-set goals and task performance of high and low self-esteem individuals. Organizational Behavior and Human Decision Processes, 70(1): 17-26. Part Three: Applications of Motivational Approaches Chapter 9: Rewards Lawler, Edward L. 1987. The design of effective reward systems. In J. W. Lorsch (ed.), Handbook of Organizational Behavior. Englewood Cliffs, NJ: Prentice Hall, pp, 25-271. Kerr, Steven. 1995. On the folly of rewarding A, while hoping for B. Academy of Management Executive, 9(1): 7-14. Pearce, Jone L. 1987. Why merit pay doesn't work: Implications from organizational theory. In D. B. Balkin and L. R. Gomez-Mejia (eds.), New Perspectives on Compensation, pp. 169-178. Pfeffer, Jeffrey. 1998. Six dangerous myths about pay. Harvard Business Review, May-June, 109-119. Duncan, W. Jack. 2001. Stock ownership and work motivation. Organizational Dynamics, 30(1): 1-11. Chapter 10: Punishment George, Jennifer M. 1995. Asymmetrical effects of rewards and punishments: the case of social loafing. Journal of Occupational and Organizational Psychology, 68: 327-338. Butterfield, Kenneth D., Trevino, Linda K., and Ball, Gail A. 1996. Punishment from the manager's perspective: A grounded investigation and inductive model. Academy of Management Journal, 39(6): 1479-1512. Chapter 11: Motivating Creativity aand Innovation Amabile, Teresa. 1997. Motivating creativity in organizations: On doing what you love and loving what you do. California Management Review, 40(1): 39-58. Cummings, Anne and Oldham, Greg R. 1997. Enhancing creativity: Managing work contexts for the high potential employee. California Management Review, 40(1): 22-38.

1,214 citations