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In this chapter, the authors consider the progress and present state of star scholarship, while planting seeds for future inquiry where we believe fruitful opportunities await – both in furthering our understanding of stars and in more effectively situating this understanding in the talent management literature. Following a reflection on the multiple conceptualizations of stars that have been proposed and employed in star research in recent years, we suggest that the most useful conceptualization of stars is one that focuses simply on stars’ exceptional contributions to value creation – allowing the specific mechanisms of value creation to vary, as they do, across contexts. Next, the authors review recent progress in star scholarship – highlighting advances in scholarship on both the favorable and unfavorable influences of stars in organizations, as well as recent research shedding light on the professional experiences of stars as employees. The authors then turn their attention to future scholarship, specifically noting opportunities for research in two veins: how stars’ motivations, contributions, and experiences may evolve over the course of their careers and how stars and their broader work environments are best managed. Finally, we share thoughts on ways in which scholars can think about increasing the practical value of research on stars, primarily by integrating insights from research on stars with ideas rooted more squarely in the talent management literature which focuses on the deliberate identification, support, and management of individuals deemed to be equipped to create exceptional value in organizations.

The purpose of this paper is to investigate the effects of social network sites (SNS) overload on individual job performance and discontinuous usage intention.

Based on the Stressor-Strain-Outcome (SSO) framework, a research model was proposed and tested empirically. The partial least squares structural equation modeling (PLS-SEM) method was applied to data collected online through a questionnaire.

Findings highlighted that social overload is related positively to information overload and communication overload. Information overload affected only the perception of work overload, while communication overload was a significant stressor affecting work overload and dissatisfaction towards SNS. Although results revealed a positive relationship between these two strains, only dissatisfaction influenced job performance and discontinuous usage intention.

As much as SNS are a useful tool in the workplace, they can have significant drawbacks. Prior studies have investigated this dark side. However, they scantily explored the effects of SNS overload on both job performance and discontinuous usage intention. Moreover, the relationships between types of overload are understudied. This paper proposes an enrichment of the literature by validating a model of the relationships between information overload, communication overload and social overload, job performance and discontinuous usage intention. It extends prior research on SNS stressors and points out the communication overload as the main SNS stressor affecting strains in the workplace.

Looks at the main provisions within the Americans with Disabilities Act and suggests that its main drawback is vagueness. States that this will only be solved as case law is added to provide clearer guidance on specific issues.

With the development of the modern portfolio theory and the advancement of information technology, the employment of quantitative approaches to practically measure asset risks and returns, and the construction of portfolios (even dynamic portfolios) has become possible and popular. Therefore, the purpose of this paper is to construct a multi‐factor model for Taiwan stock universe using fundamental technical descriptors and then to apply the equity market neutral investing using multiple‐factor models as a tool.

This study constructs a Taiwan equity multi‐factor model using cross‐sectional fundamental technical approach.

The model involves 28 explanatory factors (including 20 industry factors), and the results of the estimations are satisfactory. The model's explanatory power is 58.6 per cent on average. Furthermore, this multi‐factor model is feasible, modulized, dynamic (i.e. modified over time) and updating.

The multi‐factor model, constructed and utilized in this study, is a useful and feasible tool. It generates important inputs into the applications of building market neutral portfolio.

Taiwan OTC market is an electronic, order driven, call market. The purpose of this paper is to gain understanding of whether trade size or number of transaction provides more information on explaining price volatility and market liquidity in this market. The paper also aims to investigate how market condition can affect the relationship between information type and trading activities.

The paper uses data from the Taiwan OTC market to run the empirical tests. It divides firms into five size groups based on their market capitalization. Regression equations are run to test: whether number of transactions has a more significant impact on price volatility on the Taiwan OTC market; the impact of market information on number of transactions; the relative impact of firm specific and market information on number of transactions; and the impact of number of transaction of bid‐ask spread.

Findings show that the larger the number of transactions, the higher the price volatility. Smaller firms on the Taiwan OTC market are traded based on firm‐specific information. This relation is further affected by market trends. Especially for the larger firms, when the market is up and the amount of market information increases, number of transactions increases. When the market is down and the amount of market information increases, number of transactions decreases. Finally, it is found spread size is more likely to be influenced by number of transactions, instead of trade size. Overall, based on these empirical results, the information content of number of transactions seems to be higher than that of trade size in the Taiwan OTC market.

Investors now understand that number of transaction actually carry more information than trade size does.

The relation between market information and number of transaction, also that between market information and trade size is influenced by market condition. The paper fills a gap in the literature to show that market condition has an impact on the relation between information type and trader's behavior. A number of transactions are identified that provide more information than trade size does. It is also shown that market conditions can further affect the impact of information on trading activities.

The purpose of this paper is to present a systematic literature review on stimulus, organism and response variables related to actual and perceived cleanliness and develop a conceptual framework to encourage future research on cleanliness.

The PRISMA statement methodology for systematic literature review was applied. After analysing 926 articles, 46 articles were included and reviewed.

Stimulus, organism and response variables related to cleanliness were identified and integrated in a conceptual framework. A distinction was made between articles evaluating the relationship between stimulus and organism variables; stimulus and response variables; and organism and response variables. First, actual cleanliness, staff behaviour, condition of the environment, scent and the appearance of the physical environment were identified as stimuli variables influencing perceived cleanliness and service quality. Second, the presence of litter, behaviour and presence of others, scent, disorder, availability of trash cans and informational strategies were identified as stimuli affecting littering and other kinds of unethical behaviour. Third, the effect of perceived cleanliness (and other organism variables) on satisfaction, approach behaviours, physical activity and pro-social behaviour was registered.

The findings of this review allow in-house and corporate facility managers to better understand and identify most effective interventions positively influencing actual and perceived cleanliness.

No systematic literature review on antecedents and consequences of a clean environment has previously been conducted.

In this age of extremely well-developed social media, it is necessary to detect any change in the corporate image of an enterprise immediately so as to take quick action to avoid the wide spread of a negative image. However, existing survey-based corporate image evaluation methods are costly, slow and static, and the results may quickly become outdated. User comments, news reports and we-media articles on the internet offer varied channels for enterprises to obtain public evaluations and feedback. The purpose of this study is to effectively use online information to timely and accurately measure enterprises’ corporate images.

A new corporate image evaluation method was built by first using a literature review to establish a corporate image evaluation index system. Next, an automatic text analysis of online public information was performed through a topic classification and sentiment analysis algorithm based on the dictionary. The accuracy of the topic classification and sentiment analysis algorithm is then calculated. Finally, three internet enterprises were chosen as cases, and their corporate image was evaluated.

The results show that the author’s corporate image evaluation method is effective.

First, in this study, a new corporate image evaluation index system is constructed. Second, a new corporate image evaluation method based on text mining is proposed that can support data-driven decision-making for managers with real-time corporate image evaluation results. Finally, this study improves the understanding of corporate image by generating business intelligence through online information. The findings provide researchers with specific and detailed suggestions that focus on the corporate image management of emerging internet enterprises.

The purpose of this paper is to develop a model to examine the female consumer’s intention to shop online. The rising number of female online shoppers has compelled the analysts and online vendors to believe that understanding the attitude and behaviour of the female consumers is very crucial for their growth.

A conceptual model is proposed that expands the theory of reasoned action (TRA) with three additional constructs, namely, trust, convenience and customer service. The proposed model is examined with the help of questionnaire responses collected from 909 online shoppers from India.

The paper empirically shows that there is a significant influence of attitude, convenience, customer service and subjective norm on the female consumer’s intention to buy online. Customer service acts as the most crucial factor in influencing the attitude of female consumers towards online shopping. The paper also points out that trust does not directly affect the female’s intention to shop online but indirectly influences it through attitude.

The paper has significant implications for practitioners. First, the results advocate that convenience and customer service are the vital antecedents to both behavioural intention and behavioural attitude. Second, the paper also showcases that trust influences behavioural intention indirectly through attitude, stressing the need for the online retailers to develop consumers’ trust in online shopping.

The paper examines TRA framework in the context of female online shopping, while earlier studies have concentrated completely on efficiency-based software tools like word processing, spreadsheets, etc. The integration of the three constructs – trust, convenience and customer service – in the TRA framework has not been studied in the past. The interaction effect of the different elements of customer services on the female consumer behaviour has never been examined in the previous research works.

The purpose of this paper is to empirically test a research model that incorporated antecedents of praise feedback behaviour (fear of confrontation and incentive for reducing nuisance costs), praise feedback behaviour (deliberatively praise feedback, casual praise feedback, and true compliment feedback) and consequences (trust and repurchase intention).

A structural equation model was employed to test the relationships of the research model using survey data collected from 398 Taobao consumers.

The results showed that fear of confrontation and incentive for reducing nuisance costs had a significant positive influence on deliberatively praise feedback and true compliment feedback, respectively, and both antecedents had a significant positive influence on casual praise feedback of consumers. It also showed that trust was influenced negatively by deliberatively praise feedback, and positively by casual praise feedback and true compliment feedback. Meanwhile, deliberatively praise feedback and true compliment feedback were found to have negative and positive influences on repurchase intention, respectively.

This research was a pilot study to identify a three-dimension conceptualization of praise feedback behaviour from the perspective of customer satisfaction, and to understand positive review bias from the perspective of input processes.

The purpose of this study is to explore a sustainable hierarchical framework for the business environment in smart cities. However, this hierarchical framework must consider unnecessary attributes and interrelationships between criteria to capture the difference between smart cities and traditional cities.

Hence, the fuzzy set theory is used for screening unnecessary attributes, the decision-making and trial evaluation laboratory (DEMATEL) is applied to manage the complex interrelationships among the aspects and attributes and interpretive structural modeling (ISM) is used to divide the hierarchy and construct a hierarchical theoretical framework. Ultimately, this research is applied to develop a sustainable hierarchical framework of the business environment in smart cities.

The results show that traditional social problems are still at the core of business environment development in smart cities, new smart opportunities may be discovered, but they are still limited by traditional social factors, the economy is still the main aspect of the business environment and there are still obstacles to solving social problems with smart technologies.

This theoretical hierarchical framework aims to guide smart cities toward sustainability. This study also proposes creating a predictable business environment by improving administrative efficiency, transparency, social mobility and infrastructure services and cultivating new business opportunities with intelligent technology.

The purpose of this paper is to explore the extent to which customers evaluate inferior product presentations on a local shopping platform based on the retailer (small and medium-sized enterprise [SME] vs retail chain).

The authors conducted a between-subject online study (N = 728) with a 2 (SME vs retail chain) x 2 (high vs low-quality product presentation) between-subject experimental design. The authors conducted several analyses of variance to analyze the hypotheses and analyses of covariance for a mediating effect.

This study's results show that customers tend to overlook inaccuracies from a retail chain more often than they overlook inaccuracies from SME retailers. The authors show that the perceived competence of the retailer mediates the impact of the retailer's quality on customer purchasing intentions, not only for the presented product but also for the retailer itself.

Based on this study's results, the authors give implications for retailer cross-channel strategies and hint at the importance of emphasizing the retail size.

This paper provides important contributions to the literature on resource-advantage theory by explaining that consumers perceive quality differences within product presentations on online shopping platforms differently with regard to retail chains vs SME retailers. Moreover, the information processing theory helps to provide a theoretical foundation concerning differences in online store quality (via engineered low- vs high-quality product presentations in this study).