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Graduate employability is a key concern for many observers particularly at a time when education is increasingly available for the masses. The purpose of this paper is to examine the impact of graduate perceived employability on job search by integrating theory of planned behavior and to identify how job search self-efficacy, subjective norms, intention and intensity change over time.

Data were collected from a six-wave survey study with a sample of Chinese university graduating students.

Results show that perceived employability has a positive and significant effect on job search self-efficacy, attitude, intention and intensity; and that all the repeated measuring variables (except job search attitude) decreased over time.

The study is useful for educators, employers and prospective students. It prompts discussion of reforms in the curriculum to increase graduate awareness of the complexity of the job search process and existing opportunities. The study could also help to explain how job search behavior changes over time.

The findings carry implications for both higher education research and the measures of improving graduate employability. The study fills the gap in the literature by integrating employability and the theory of planned behavior into one framework in order to analyze the process of Chinese university graduates’ job search behavior.

This research aims to examine the relationship of personal innovativeness, perceived value (consisting of perceived utilitarian and hedonic value) and continuance intention in the context of ride-hailing apps and to investigate consumer behaviour differences between metro and non-metro consumers.

The survey sample included 402 consumers of popular ride-hailing apps in Indonesia to test the research framework. Then, PLS-SEM-based software was utilised to examine the hypothesised relationship.

The findings indicate that the effect of personal innovativeness on continuance intention in using ride-hailing apps will operate through the full mediation role of perceived hedonic and utilitarian value, respectively. The findings also show that there are consumer behaviour differences between metro and non-metro consumers, in which the cognitive belief of consumers in the metro areas regarding the usage of ride-hailing apps is more related to hedonic value.

The variety of respondent demographic profiles in this research is limited in that most of the research respondents are students. In such a case, the study may face the issue of generalisation.

This research generates an extended idea of the information technology continuance model by validating the important role of perceived hedonic and utilitarian value as an integral part of the model and strengthens the insights that Indonesia has consumer behaviour differences regarding technology-based services, particularly ride-hailing apps, between metro and non-metro consumers.

In the era of digitalization and technology, tremendous changes have taken place in the taxi industry worldwide. The traditional taxi service has transformed into the latest innovative technology-based e-hailing service. There are innumerable factors that drive the user adoption of e-hailing apps. This study aims to primarily concentrate on identifying, analyzing and ranking these factors which have an impact on the user intention toward using e-hailing apps.

The e-hailing app users in the state of Punjab and Chandigarh are the target population for the study. A fuzzy analytical hierarchy process technique has been applied to analyze and codify the determinants that influence the user intention of adopting e-hailing apps. The primary factors that have been considered for the study are social influence, perceived usefulness, facilitating conditions, perceived ease of use, self-efficacy, perceived risk, compatibility and trust.

The study revealed that “Perceived Usefulness” is the factor that influences user intention to use e-hailing apps the most, while “Perceived Risk” the least. The sub-criteria codified in the top priority was as follows: “Overall, I find the e-hailing app useful in booking a taxi (C15)”; “I do not need some people to use e-hailing apps (C52); “I believe e-hailing app is compatible with existing technology (C61).” The sub-criterion “E-hailing app service provider keeps its promise (C72)” was demonstrated to have the least impact on the user intention of adopting e-hailing apps.

The study has been confined to only eight factors selected from the extended technological acceptance model framework and some related technology acceptance theories. Some more other factors may have an impact on user adoption of e-hailing apps, which need to be added further. Also, the scope of the study should be enhanced by expanding the geographical area beyond the selected region.

The findings of the study enable the e-hailing service providers and marketers to understand the users’ intention in a better way, to make improvements in e-hailing apps and formulate strategies accordingly.

The previous literature provides the base to the present study for identifying the factors affecting user behavioral intention toward e-hailing apps and information technology. The findings and results of the present research make value addition to the existing knowledge base.

Algorithms are widely used to manage various activities in the gig economy. Online car-hailing platforms, such as Uber and Lyft, are exemplary embodiments of such algorithmic management, where drivers are managed by algorithms for task allocation, work monitoring and performance evaluation. Despite employing substantially, the platforms face the challenge of maintaining and fostering drivers' work engagement. Thus, this study aims to examine how the algorithmic management of online car-hailing platforms affects drivers' work engagement.

Drawing on the transactional theory of stress, the authors examined the effects of algorithmic monitoring and fairness on online car-hailing drivers' work engagement and revealed the mediation effects of challenge-hindrance appraisals. Based on survey data collected from 364 drivers, the authors' hypotheses were examined using partial least squares structural equation modeling (PLS-SEM). The authors also applied path comparison analyses to further compare the effects of algorithmic monitoring and fairness on the two types of appraisals.

This study finds that online car-hailing drivers' challenge-hindrance appraisals mediate the relationship between algorithmic management characteristics and work engagement. Algorithmic monitoring positively affects both challenge and hindrance appraisals in online car-hailing drivers. However, algorithmic fairness promotes challenge appraisal and reduces hindrance appraisal. Consequently, challenge and hindrance appraisals lead to higher and lower work engagement, respectively. Further, the additional path comparison analysis showed that the hindering effect of algorithmic monitoring exceeds its challenging effect, and the challenge-promoting effect of algorithmic fairness is greater than the algorithm's hindrance-reducing effect.

This paper reveals the underlying mechanisms concerning how algorithmic monitoring and fairness affect online car-hailing drivers' work engagement and fills the gap in the research on algorithmic management in the context of online car-hailing platforms. The authors' findings also provide practical guidance for online car-hailing platforms on how to improve the platforms' algorithmic management systems.

The online platform is one of the essential components of the platform economy that is constructed by a large scale of the personal data resource. However, accurate empirical test of the competition structure of the data-driven online platform is still less. This research is trying to reveal market allocation structure of the personal data resource of China's car-hailing platforms competition by the empirical data analysis.

This research is applying the social network analysis by R packages, which include k-core decomposition and multilevel community detection from the data connectedness via the decompilation and the examination of the application programming interface of terminal applications.

This research has found that the car-hailing platforms, which establish more constant personal data connectedness and connectivity with social media platforms, are taking the competitive market advantage within the sample network. Data access discrimination is a complementary method of market power in China's car-hailing industry.

This research offers a new perspective on the analysis of the multi-sided market from the personal data resource allocation mechanism of the car-hailing platform. However, the measurement of the data connectedness requires more empirical industry data.

This research reveals the competition structure that relies on personal data resource allocation mechanism. It offers empirical evidence for governance, which is considered as the critical issue of big data research, by reviewing the nature of the data network.

It also reveals the data convergence process of the social system and the technological system.

This research offers a new research method for the real-time regulation of the car-hailing platform.

Despite the perceived role of customer value in post-adoption behaviour in the context of ride-hailing apps such as Uber, there has been limited research on the subject. This paper seeks to enrich the understanding of the relationships between customer perceived value, particularly hedonic value and economic value, customer satisfaction and continued use intentions of ride-hailing apps.

This analysis is based on field data collected from 567 users of ride-hailing apps in Ghana. Data collected from the survey were analysed using the partial least square (PLS) approach to structural equation modelling (SEM).

The paper provides evidence that hedonic value, as well as economic value, positively predicts customer satisfaction and continued use intentions of ride-hailing apps. Further analysis reveals customer satisfaction directly predicts continued use intentions in addition to partially mediating the influence of customer perceived value on continued use intentions of ride-hailing apps. Finally, the findings suggest that hedonic value has a stronger impact on continued use intentions than economic value, while economic value has a greater impact on satisfaction than hedonic value.

The study contributes to post-adoption behaviour research by providing evidence on the relationships among the study constructs in a developing country context. Overall, the findings will stimulate future empirical debates on the subject and guide practitioners in decision-making concerning customers' usage of ride-hailing apps.

Mobile taxi booking apps (MTB) have revolutionalized the transportation industry. As taxis can be hired via smartphones, irrespective of any time or place, the business platform for taxi service has completely changed. Now customers are saved from the hassle of going to the designated taxi stands or waiting along the roadside. But, the long-term sustainability of this service depends on its continued use. Therefore, this study aims to explore factors that hedonically incline people toward continuance of MTB. To achieve the purpose, the unified theory of acceptance and use of technology (UTAUT) was extended with mediation effects of hedonic motivation.

The data were collected from existing users of MTB and analyzed through structural equation modeling and revalidated via artificial neural networks.

The statistical results show that the main factors of UTAUT substantially create hedonic motivation to use the apps and significantly mediate their effects on behavioral intention to continue using MTB. However, mediation between social influence and continuity intent was not statistically supported. The findings represent important contributions to the extended UTAUT.

This study adds value to the theoretical horizon and also presents M-taxi companies with useful and pertinent plans for efficient designing and effective implementation of MTB. Moreover, limitations and suggestions for future researchers are also discussed.

This study extends UTAUT with the mediating role of hedonic motivation to predict continued use of MTB, which further initiates the applicability of UTAUT in a new setting and a new perspective (post adoption). This, in turn, significantly expands theory by using hedonic motivation as an important attribute that could mediate impact of all main antecedents to shape customers loyalty toward system use.

The study aims at reviewing a synthesis of disclosure, transparency, and International Financial Reporting Standards (IFRS) implementation in an attempt to provide directions for future research. Prior research overwhelmingly supports that the IFRS adoption or effective implementation of IFRS will enhance high-quality financial reporting, transparency, enhance the country’s investment environment, and foreign direct investment (FDI) (Dayanandan, Donker, Ivanof, & Karahan, 2016; Gláserová, 2013; Muniandy & Ali, 2012). However, some researchers provide conflicting evidence that developing countries implementing IFRS are probably not going to encounter higher FDI inflows (Gheorghe, 2009; Lasmin, 2012). It has also been argued that the IFRS adoption decreases the management earnings in countries with high levels of financial disclosure. In general, the study indicates that the adoption of IFRS has improved the financial reporting quality. The common law countries have strong rules to protect investors, strict legal enforcement, and high levels of transparency of financial information. From the extensive structured review of literature using the Scopus database tool, the study reviewed 105 articles, and in particular, the topic-related 94 articles were analysed. All 94 articles were retrieved from a range of 59 journals. Most of the articles (77 of 94) were published 2010–2018. The top five journals based on the citations are Journal of Accounting Research (187 citations), Abacus (125 citations), European Accounting Review (107 citations), Journal of Accounting and Economics (78 citations), and Accounting and Business Research (66 citations). The most-cited authors are Daske, Hail, Leuz, and Verdi (2013); Daske and Gebhardt (2006); and Brüggemann, Hitz, and Sellhorn (2013). Surprisingly, 65 of 94 articles did not utilise the theory. In particular, four theories have been used frequently: agency theory (15), economic theory (5), signalling theory (2), and accounting theory (2). The study calls for future research on the theoretical implications and policy-related research on disclosure and transparency which may inform the local and international standard setters.

This paper aims to identify the dimensions of service quality in the case of ride-sourcing services in Indian context.

The service quality dimensions of ride-sourcing services are identified using an exploratory factor analysis (EFA). Further, the reliability and validity of the factors are established through confirmatory factor analysis (CFA) using AMOS.

The service quality dimensions of ride-sourcing services are identified: comfort, internal environment, safety and personnel, mobile convenience and reliability, mobile system efficiency and availability, mobile customer service and billing and mobile security and privacy.

The various dimensions are identified to measure service quality of ride-sourcing services in India. So, these dimensions can be tested for ride-sourcing services of countries having similar culture as India.

The proposed dimensions can be used as a diagnostic tool to identify and compare important criteria for service quality of ride-sourcing services.

Most relevant studies about dimensions of service quality for ride-sourcing services do not have stable factor structure. The dimensions identified include the traditional taxi service quality and mobile app service quality, which are not covered in current literature.

The fundamental change in accounting rules for equity-based compensation (EBC) instituted by SFAS 123, SFAS 123r, and IFRS 2 has allowed for new insights related to a variety of research questions. This paper discusses the empirical evidence generated in the wake of the new regulation and categorizes it into two broad streams. The first stream encompasses research on the changed use of EBC and the incentives provided. The second stream addresses how firms account for EBC, including the underreporting phenomenon and how it was affected by the mandatory recognition of EBC expenses. I discuss where research delivers unanimous findings versus contradictory results. Using these insights, I make recommendations for further research opportunities in the area of EBC.