Search results

To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.

Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.

Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.

This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.

Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.

In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.

Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.

Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.

One of the issues currently being discussed around the globe, and especially in the tourism industry, is revisit intention. This study uses a bibliometric analysis strategy based on the Web of Science (WOS) database to examine the literature on revisit intention.

In this study, a sample of 482 articles was analyzed. The R programming language was used to process the data and graph the results.

The results found the occurrence of publications by year, publication source information and authors, journals, countries, institutions, thematic maps, current trends of topics in hospitality and tourism toward revisiting intention, and the most cited papers in revisit intention. This study highlights the importance of revisiting intention in the hospitality and tourism industry. The bibliometric analysis helps to set the research agenda on revisit intention.

To the best of the authors’ knowledge, this is the first study of its kind to present an empirical evaluation of revisit intention using inclusive mapping.

Self-presentation is an important aspect of influencer marketing. Drawing upon self-presentation theory and source credibility theory, this study aimed to unravel how the self-presentation strategies of a layperson, opinion leadership and micro-celebrity influence source credibility (i.e. trustworthiness, expertise, physical attractiveness and social attractiveness) and how source credibility, in turn, affects brand responses.

An online experiment among female participants (N = 229) was conducted. Participants were shown a sponsored blog in which the influencer presented herself as either a layperson, an opinion leader or a micro-celebrity.

The study demonstrated that the presentation strategy of a layperson was more persuasive than a micro-celebrity presentation because of higher levels of (1) trust and (2) social attractiveness. In addition, opinion leaders were perceived as having more expertise than laypeople and, therefore, positively enhanced brand responses.

The current findings provide relevant insights into the theoretical mechanisms (i.e. expertise, trustworthiness and social attractiveness) that explain the effects of self-presentation strategies on brand responses.

Our findings imply that credibility perceptions determine the persuasiveness of the SMI. This study showed that layperson and opinion leadership self-presentation strategies are relatively more persuasive.

This study is the first to show that influencers’ self-presentation strategies determine how people respond to the brands that influencers promote. In addition, we show that these effects are explained by the influencers’ trust, social attractiveness and expertise.

This article aims to investigate how institutional characteristics affect the level of financial development of economies collectively and compare between developed and undeveloped economies.

A dynamic panel with 131 countries, including developed and developing ones, was utilized; the estimators of the generalized method of moments system (GMM system) model were selected because they have econometric characteristics more suitable for analysis, providing superior statistical precision compared to traditional linear estimation methods.

The results from the full panel suggest that concrete and well-defined institutions are important for financial development, confirming previous research, with a more limited scope than the present work.

Limitations of this research include the availability of data for all countries worldwide, which would make the research broader and more complete.

A panel of countries was used, divided into developed and developing countries, to analyze the impact of institutional variables on the financial development of these countries, which is one of the differentiators of this work. Another differentiator of this research is the presentation of estimates in six different configurations, with emphasis on the GMM system model in one and two steps, allowing for comparison between results.

Engaged employees assure organizational competitiveness and sustainability. The purpose of this study is to explore the relationship between job resources and employee turnover intentions, with employee engagement as a mediating variable.

Data were collected from 934 employees of eight wholly-owned pharmaceutical industries. The proposed model and hypotheses were evaluated using structural equation modeling. Construct reliability and validity was established through confirmatory factor analysis.

Data supported the hypothesized relationship. The results show that job autonomy and employee engagement were significantly associated. Supervisory support and employee engagement were significantly associated. However, performance feedback and employee engagement were nonsignificantly associated. Employee engagement had a significant influence on employee turnover intentions. The results further show that employee engagement mediates the association between job resources and employee turnover intentions.

The generalizability of the findings will be constrained due to the research’s pharmaceutical industry focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers in the pharmacuetical industry to develop a proactive and well-articulated employee engagement intervention to ensure organizational effectiveness, innovativeness and competitiveness.

By empirically demonstrating that employee engagement mediates the nexus of job resources and employee turnover intentions, the study adds to the corpus of literature.

This study builds on the panarchy theory by viewing the supply chain as a socio-ecological system and further expands it by considering the within-level linkages internal to the supply chain level. Three types of linkages are considered: the two cross-level linkages with the planetary and the political-economic levels and the supply chain within-level linkages. The research questions are addressed using the data gathered by the Carbon Disclosure Project within its Supply Chain Programme.

This work aims to study, applying the lens of panarchy theory, how the planetary and the political-economic levels affect the supply chain within-level linkages for sustainability. Furthermore, the difference in how these cross-level linkages influence focal firms and first-tier suppliers is explored.

The results show that considering the planetary-supply chain linkage, climate change risk exposure is likelier to foster within-level linkages with buyers than with suppliers. Further, climate change mitigation investments have different roles in the different tiers: focal firms are pushed to strengthen the linkages with their suppliers when they lose efficacy in improving their carbon performance, whereas first-tier suppliers exploit investments to gain legitimacy. Discussing the political-economic level effect, perceptions from first-tier suppliers could be two-fold: they could perceive a mandating power mechanism or exploit policymakers’ knowledge to advance their capabilities.

The results contribute to the sustainable supply chain management literature by providing empirical evidence of the cross-level linkages theorised by the panarchy theory. Moreover, the concept of within-level linkages is proposed to apply the theory in this field.

The study seeks to understand the possible opportunities that Industry 5.0 might offer for various aspects of inclusive sustainability. The study aims to discuss existing perspectives on the classification of Industry 5.0 technologies and their underlying role in materializing the sustainability values of this agenda.

The study systematically reviewed Industry 5.0 literature based on the PRISMA protocol. The study further employed a detailed content-centric review of eligible documents and conducted evidence mapping to fulfill the research objectives.

The advancement of Industry 5.0 is currently underway, with noteworthy initial contributions enriching its knowledge base. Although a unanimous definition remains lacking, diverse viewpoints emerge concerning the recognition of fundamental technologies and the potential for yielding sustainable outcomes. The expected contribution of Industry 5.0 to sustainability varies significantly depending on the context and the nature of underlying technologies.

Industry 5.0 holds the potential for advancing sustainability at both the firm and supply chain levels. It is envisioned to contribute proportionately to the three sustainability dimensions. However, the current discourse primarily dwells in theoretical and conceptual domains, lacking empirical exploration of its practical implications.

This study comprehensively explores diverse perspectives on Industry 5.0 technologies and their potential contributions to economic, environmental and social sustainability. Despite its promise, the practical evidence supporting the effectiveness of Industry 5.0 remains limited. Certain conditions are necessary to realize the benefits of Industry 5.0 fully, yet the mechanisms behind these conditions require further investigation. In this regard, the study suggests several potential areas for future research.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

The reemergence of immersive virtual technology (IVR) provides both opportunities and challenges for workplace learning (WPL). The purpose of this study is to explore and develop knowledge about how gamification influences the WPL experience by addressing two research questions: RQ1. What characterizes a gamified immersive safety training experience with IVR technology? and RQ2. How does gamified immersive safety training with IVR technology impact the WPL experience?

The study adopted a mixed methods approach by combining a systematic literature review with a case study on an empirical project about immersive fire safety training for train operators that are used at the Swedish train operating company SJ. The case study included data from semistructured interviews, Web survey and observation studies. The data was analyzed in two stages combining inductive and deductive data analysis for identifying themes and categories.

The findings of the study are twofold: (1) themes that conceptualize the gamified immersive safety training experience based on outputs from both the literature review and the first round of data analysis; and (2) a framework with three overarching categories that are mapped with the identified themes, and which were deduced throughout the second round of data analysis.

The originality of the findings stresses the implications of how a body of knowledge that synthesizes gamification concepts with immersive safety training, can inform the design of WPL experiences that are facilitated with IVR technology. As such, the implications of the findings are targeted toward both the advancement of the IVR discourse in the WPL field, but also toward practical considerations for design of immersive learning experiences that enrich WPL practices and culture.