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The purpose of this paper is to consider queuing systems where captive repeat customers select a service facility each period. Are people in such a distributed system, with limited information diffusion, able to approach optimal system performance? How are queues formed? How do people decide which queue to join based on past experience? The authors explore these questions, investigating the effect of information availability, as well as the effect of heterogeneous facility sizes, at the macro (system) and micro (individual performance) levels.

Experimental economics, using a queuing experiment.

The authors find little behavioural difference at the aggregate level, but observe significant variations at the individual level. This leads the authors to the conclusion that it is not sufficient to evaluate system performance by observing average customer allocation and sojourn times at the different facilities; one also needs to consider the individuals’ performance to understand how well the chosen design works. The authors also observe that better information diffusion does not necessarily improve system performance.

Evaluating system performance based on aggregate behaviour can be misleading; however, this is how many systems are evaluated in practice, when only aggregate performance measures are available. This can lead to suboptimal system designs.

There has been little theoretical or empirical work on queuing systems with captive repeat customers. This study contributes to the understanding of decision making in such systems, using laboratory experiments based on the cellular automata approach, but with all agents replaced by humans.

Social commerce is a subpart of electronic commerce (e-commerce), where social media is forced to support user contributions. The purpose of this study is to measure the impact of customers' interpersonal interactions in social commerce on customer relationship management (CRM) performance, based on the flow, commitment-trust and stimulus–organism–response (SOR) theories.

On the basis of the SOR framework, the authors developed a study model to determine the impact on CRM performance of customers' interpersonal interactions in social commerce. The primary data of the study were collected from 640 users of social commerce through a web questionnaire during the COVID-19 (coronavirus disease 2019) pandemic situation, and the authors tested the study model using the approach of covariance-based structural equation modeling (SEM).

Results of the current study reveal that customers' interpersonal interactions in social commerce optimistically influence their perceived flow. Moreover, perceived flow absolutely controls users' trust and CRM performance. In turn, collective users' trust positively influences users' commitment and CRM performance. Finally, collective users' commitment absolutely influences the performance of CRM.

The authors provide a valuable contribution to the theoretical field of online marketing and CRM. Besides, the findings of this study are relevant for marketers to know the issues for increasing customer trust, commitment and performance of CRM.

The current study develops a model based on the flow, commitment-trust and stimulus–organism–response (SOR) theories. The authors' research is the first to estimate the effect of customers' interpersonal interactions in social commerce on CRM performance.

The paper aims to explore how power and gender influence decision making in an operational and risky context.

The authors run a laboratory experiment. The experimental factors are power and operational profitability. Power is manipulated using an episodic priming task, while profitability, by changing a newsvendor-type product’s procurement cost. Participants’ risk attitude is captured using a risk lottery.

Participants deviate from the optimal order regardless of the power condition and their risk profile. Risk-seeking women order consistently more than risk-seeking men, which allow women to offer a higher service level. In the low-profit condition, men prefer to make more conservative decisions, which allow them to place orders that are closer to the economical benchmark, where both men’ induced power and the risk-seeking tendencies from both genders play a role. Behavioural models in the high-power condition explain the observed differences in ordering behaviours.

This paper provides behavioural research to explore how differences in power and gender, and their links with risky decision making, influence decision making in an uncertain operations management context, representing thus an important departure from mainstream studies.

The purpose of this paper is to investigate the impact of buyer-seller interpersonal interactions on the purchase intention of buyers, incorporating swift guanxi as a mediator.

Based on survey data obtained from 336 Taobao Live users, PLS techniques were used to test hypotheses.

Swift guanxi exists in buyer-seller interactions and matters, as it drives buyers' purchase intention in live stream shopping. Perceived expertise, perceived similarity and perceived likeability are found to be the three essential interpersonal interaction factors promoting the formation of swift guanxi. Perceived familiarity is also found to be significant but to a lesser extent. In addition, all these interpersonal interaction factors are found to significantly affect purchase intention through the mediation of swift guanxi.

Swift guanxi has been less explored in live stream shopping. This study takes the lead in empirically examining the mediating role of swift guanxi in the relationship between interpersonal interaction factors and purchase intention and offers a description of key buyer-seller interpersonal interaction factors (perceived expertise, perceived similarity and perceived likeability), thereby helping to extend the swift guanxi literature in social commerce.

This study seeks to extend previous research on experts with mainly ad‐hoc groups from laboratory research to a field setting. Specifically, this study aims to investigate experts' relative importance in team performance. Expertise is differentiated into two categories (task functions and team functions) and the paper aims to investigate whether experts in task and team functions predict team performance over and above the team's average expertise level.

Longitudinal, multi‐source data from 96 professional software design engineers were used by means of hierarchical regression analyses.

The results show that both expert members in task functions (i.e. behavior that aids directly in the completion of work‐related activities) and the experts in team functions (i.e. facilitation of interpersonal interaction necessary to work together as a team) positively predicted team performance 12 months later over and above the team's average expertise level.

Samples from other industry types are needed to examine the generalizability of the study findings to other occupational groups.

For staffing, the findings suggest that experts are particularly important for the prediction of team performance. Organizations should invest effort into finding “star performers” in task and team functions in order to create effective teams.

This paper focuses on the relationship between experts (in task functions and team functions) and team performance. It extends prior research on team composition and complements expertise research: similar to cognitive ability and personality, it is important to take into account member expertise when examining how to manage the people mix within teams. Benefits of expertise are not restricted to laboratory research but are broadened to real‐world team settings.

With the prevailing microblogging phenomenon, many marketers have created their microblog accounts to promote products, advertise brands, and attract consumers. The purpose of this paper is to examine the effects of consumers’ community commitment, information technology (IT) habit, and participation on their brand loyalty in the context of enterprise microblogs.

A total of 364 valid data were collected from fans or followers of enterprise microblogs through a survey on Weibo.com. The data were analyzed with smart partial least squares.

Community commitment and IT habit directly lead to brand loyalty and indirectly affect brand loyalty through the mediating influence of participation. Information quality, perceived expertise, and social interaction are antecedents of community commitment. Satisfaction, importance, and social interaction positively affect IT habit.

To enhance the generalizability of the study, future studies may examine findings in other platforms (e.g. Twitter) with a large sample size.

Practitioners can increase consumers’ brand loyalty through enterprise microblogs. Considerable attention should be directed to facilitating members’ community commitment and IT habit. In addition, the study points out significant antecedents of community commitment and IT habit for researchers, managers, and companies.

To uncover the marketing potential of microblogging technology, the authors highlight the need for investigating how enterprise microblogs generate promising marketing outcomes. The present study examines key determinants of brand loyalty. The model empirically shows the significant effects of community commitment, IT habit, and participation.

The purpose of this paper is to examine some drivers of users’ participation in online social question-and-answer (Q&A) communities based on social cognitive theory and then identify the underlying mechanism of this process.

This study developed a research model to test the proposed hypotheses, and an online survey was employed to collected data. Totally, 313 valid responses were collected, and partial least squares structural equation modeling was adopted to analyze these data.

This study empirically finds that the outcome expectations (personal outcome expectations and knowledge self-management outcome expectations) are positively related to participation in online social Q&A communities. At the same time, users’ self-efficacy positively influences their participation behaviors. It can not only directly motivate users’ participation, but also indirectly promote participation behaviors through the two dimensions of outcome expectations. Besides, perceived expertise and perceived similarity are two positive and significant environmental elements affecting users’ participation.

This study extends the understanding about how participation behaviors will be motivated in the context of online social Q&A communities. Drawing on the social cognitive theory, constructs were established based on the features of these communities. Meanwhile, some mediating effects in the motivating process were also discussed.

Investigates the differences in protocols between arbitral tribunals and courts, with particular emphasis on US, Greek and English law. Gives examples of each country and its way of using the law in specific circumstances, and shows the variations therein. Sums up that arbitration is much the better way to gok as it avoids delays and expenses, plus the vexation/frustration of normal litigation. Concludes that the US and Greek constitutions and common law tradition in England appear to allow involved parties to choose their own judge, who can thus be an arbitrator. Discusses e‐commerce and speculates on this for the future.