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This study is intended to introduce and summarise Industry 4.0 practices in BRICS nations (the abbreviation “BRICS” is made up of the first letters of the member countries: Brazil, Russia, India, China and South Africa) and determine each nation’s current contribution to Industry 4.0 practice implementation based on past literature. As the BRICS countries continue to play an essential role in the global economy, it is significant to understand Industry 4.0, focussing on these emerging economies.

To assess the present research work on Industry 4.0 practices and research studies in BRICS nations, a systematic literature review (SLR) is performed using the articles available on the SCOPUS database. This study is a descriptive analysis based on the frequency and year of publications, the most influential universities, most influential journals and most influential articles. Similarly, this study consists of category analysis based on multi-criteria decision-making (MCDM) methods, research design used, research method utilised, different data analysis techniques and different Industry 4.0 technologies were used to solve different applications in the BRICS nations.

According to the analysis of past literature, the primary identified practices are centred on operations productivity, waste management, energy reduction and sustainable processes. It also found that despite the abundance of research on Industry 4.0, the major academic journal publications are restricted to a small number of industries and issues in which the manufacturing and automotive industries are front runners. The categorisation of selected papers based on the year of publication demonstrates that the number of publications has been rising. It is also found that China and India, out of the BRICS countries, have contributed significantly to Industry 4.0-related publications by contributing 61 percent of the total articles identified. Similarly, this study identified that qualitative research design is the most adopted framework for research, and empirical triangulation is the least adopted framework in this field. The categorisation of selected articles facilitates the identification of numerous gaps, such as that 67.14% of the literature research is qualitative.

Understanding Industry 4.0 in the BRICS nations helps to identify opportunities for international collaboration and future cooperation possibilities. This study helps to promote collaboration between BRICS countries and other nations, organisations or businesses interested in capitalising on these growing economies' assets and capabilities related to Industry 4.0 technologies. This study helps to provide essential insights into the economic, technological and societal impacts, allowing for effective decision-making and strategic planning for a sustainable and competitive future. So, this contribution links the entire world in terms of the better utilisation of resources, the reduction of downtime, improving product quality, personalised products and the development of human resource capabilities through the application of cutting-edge technologies for nearly half of the world’s population.

In this study, BRICS nations are selected due to their significant impact on the world regarding social, economic and environmental contributions. In the current review, 423 articles published up to August 2022 were selected from the SCOPUS database. The comparison analysis of each BRICS nation in the form of applications of Industry 4.0, the primary area of focus, leading industry working, industry involvement with universities and the area that needs attention are discussed. To the best of our knowledge, this is the most recent SLR and meta-analysis study about Industry 4.0 in BRICS nations, which analysed the past available literature in nine different descriptive and category-wise classifications, considering a total of 423 articles. Based on this SLR, this study makes some important recommendations and future directions that will help achieve social, economic and environmental sustainability in BRICS nations.

In order to solve the decision-making problem that the attributive weight and attributive value are both interval grey numbers, this paper tries to construct a multi-attribute grey decision-making model based on generalized greyness of interval grey number.

Firstly, according to the nature of the generalized gresness of interval grey number, the generalized weighted greyness distance between interval grey numbers is given, and the transformation relationship between greyness distance and real number distance is analyzed. Then according to the objective function that the square sum of generalized weighted greyness distances from the decision scheme to the best scheme and the worst scheme is the minimum, a multi-attribute grey decision-making model is constructed, and the simplified form of the model is given. Finally, the grey decision-making model proposed in this paper is applied to the evaluation of technological innovation capability of 6 provinces in China to verify the effectiveness of the model.

The results show that the grey decision-making model proposed in this paper has a strict mathematical foundation, clear physical meaning, simple calculation and easy programming. The application example shows that the grey decision model in this paper is feasible and effective. The research results not only enrich the grey system theory, but also provide a new way for the decision-making problem that the attributive weights and attributive values are interval grey numbers.

The decision-making model proposed in this paper does not need to seek the optimal solution of the attributive weight and the attributive value, and can save the decision-making labor and capital investment. The model in this paper is also suitable for the decision-making problem that deals with the coexistence of interval grey numbers and real numbers.

The paper succeeds in realizing the multi-attribute grey decision-making model based on generalized gresness and its simplified forms, which provide a new method for grey decision analysis.

Online employee reviews have a substantial impact on employee recruitment, retention and the overall perception of a company’s image, making them a crucial element of its online reputation. Consequently, these reviews play a vital role in shaping the company’s competitiveness in the talent market. This study aims to investigate the role of employee loyalty in online reputation in the tourism and hospitality sector.

This study collected online reviews posted by 334,428 employees across 173 companies in the tourism and hospitality sector. Then, this study proposed a method for measuring employee loyalty toward the company through text comments. Furthermore, the role of employee loyalty in online reputation through regression models was analyzed.

Employee loyalty is positively associated with the closed-form evaluations, and the length and readability of open-ended comments is directly and positively associated with review helpfulness and is indirectly associated with review helpfulness through employee online reviews. Employees’ perception of job instability has a significant moderating effect on the above relationships.

This study contributes to the literature on loyalty in the tourism and hospitality industry, online reputation and employee risk perception. These findings offer a more profound understanding of the extra-role behaviors demonstrated by loyal employees, provide a theoretical foundation for the formation of a company’s online reputation and contribute to helping the tourism and service industry better address risk events. These conclusions provide valuable insights for companies in the fields of human resource management and online reputation management.

To the best of the authors’ knowledge, this study is the first to reveal the impact of employee loyalty on the company’s online reputation and provides important theoretical and practical implications for management.

This study aims to explore the intelligibility of communication with stakeholders as a result of accrual accounting adoption. It focuses on changes in the use of visual forms and the readability of text that occurred immediately after the adoption of accrual accounting in performance reports of Italian public universities.

The authors collect the stakeholder section of performance reports published before and after accrual accounting adoption. Then, the authors use manual and computer-assisted textual analysis. Finally, the authors explore the data using principal component analysis and qualitative comparative analysis.

This study demonstrates that switching from cash to accrual accounting provokes immediate changes in communication patterns. It confirms the significant reduction of readability and increase in visual forms after accruals accounting adoption. The results indicate that smaller universities especially put effort into increasing intelligibility while implementing a more complex accounting system. This study also finds a relation between the change in readability and the change in visual forms that are complementary, with the exception of several very large universities.

The findings underline the possibility of neutralising the adverse effects of accounting reform associated with its complexity and difficulties in understanding by the use of visual forms and attention to the document’s readability.

This paper adds a new dimension to the study of public sector accounting from the external stakeholder perspective. It provides further insight into the link between accrual accounting adoption and readability, together with the use of visual forms by universities.

To increase the understanding of how entrepreneurship education impacts entrepreneurial careers, the purpose of the paper is to investigate the role that a venture creation program (VCP) might have in mitigating or surpassing a lack of other antecedents of entrepreneurial careers. In particular, the authors focus on entrepreneurial pedigree and prior entrepreneurial experience.

Data from graduates of VCPs at three universities in Northern Europe were collected through an online survey. Questions addressed graduate background prior to education, yearly occupational employment subsequent to graduation and graduates' own perceptions of entrepreneurial activity in employment positions. The survey was sent to 1,326 graduates and received 692 responses (52.2% response rate).

The type of VCP, either independent (Ind-VCP) or corporate venture creation (Corp-VCP), influenced the mitigation of prior entrepreneurial experience. Prior entrepreneurial experience, together with Ind-VCP, made a career as self-employed more likely. However, this was not the case for Corp-VCP in subsequently choosing intrapreneurial careers. Entrepreneurial pedigree had no significant effect on career choice other than for hybrid careers.

Entrepreneurial experience gained from VCPs seems to influence graduates toward future entrepreneurial careers. Evidence supports the conclusion that many VCP graduates who lack prior entrepreneurial experience or entrepreneurial pedigree can develop sufficient entrepreneurial competencies through the program.

This study offers novel evidence that entrepreneurship education can compensate for a lack of prior entrepreneurial experience and exposure for students preparing for entrepreneurial careers.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

The increasing popularity of live-streaming commerce has provided a new opportunity for e-retailers to boost sales. This study integrated signaling theory and social exchange theory to investigate how streamer- and product-centered signals influence customers’ likelihood of making an impulsive purchase in the live-streaming commerce context.

An online survey was designed and distributed to the target respondents in China using purposive sampling. A total of 735 valid responses were analyzed with partial least square structural equation modeling (PLS-SEM).

Both streamer-centered signals, i.e. streamer credibility and streamer interaction quality, were discovered to significantly influence product-centered signal, i.e. product information quality. Additionally, streamer interaction quality was found to have a significant impact on streamer credibility. Furthermore, it was observed that customer engagement played a significant mediating role in the relationship between product information quality and impulsive buying tendency. Moreover, the paths between product information quality and customer engagement, as well as the connection between engagement and impulsive buying tendency, were found to be moderated by guanxi orientation.

Despite the prevalence of impulsive purchases in live-streaming commerce, few studies have empirically investigated the impact of streamer and product signals on influencing customers’ impulsive purchase decisions. Consequently, to the best of our knowledge, this study distinguishes itself by offering empirical insights into how streamers use reciprocating relationship mechanisms to communicate signals that facilitate impulsive purchase decisions.

This study aims to explore the enabling and suppressing effects of leader affiliative and aggressive humor on employee knowledge sharing form the lens of emotional contagion process, which provides theoretical reference for the applications of different leader humor style, thereby enhancing employee knowledge sharing.

This study collected three waves of data and surveyed 379 employees in China. Regression analysis, bootstrapping and latent moderation structural equation were adopted to test the hypotheses.

Leader affiliative humor has a positive impact on employee knowledge sharing, whereas leader aggressive humor has a negative impact on employee knowledge sharing. Positive emotion plays a mediating role between leader affiliative humor and employee knowledge sharing, and negative emotion plays a mediating role between leader aggressive humor and employee knowledge sharing. Moreover, supervisor–subordinate Guanxi moderates the relationship between leader affiliative humor and positive emotion, and between leader aggressive humor and negative emotion, respectively.

This study not only adds to the knowledge sharing literature calling for the exploration of antecedents and mechanism of employee knowledge sharing, but also contributes to our comprehensive understanding of the suppressing and enabling effects of leader humor style on employee knowledge sharing. Besides, this study also unpacks the dual-path mechanism and boundary condition between leader humor style and employee knowledge sharing and augments the theoretical explanations of emotional contagion theory between leader humor style and employee knowledge sharing.

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

The paper provides a step-by-step guide in the guise of a roadmap for service improvement initiatives using importance performance map analysis (IPMA).

To empirically illustrate how IPMA can be applied to any service industry, three sectors are considered; sports and fitness (study A), hospitality (study B) and higher education (study C). Following the proper selection of measuring instruments and their evaluation using structural equation modeling-partial least squares (Smart-PLS), IPMA is applied to identify those attributes having strong total effects (high importance) over the targeted construct (satisfaction) but which also have low average latent variable scores (low performance).

For sports and fitness (study A), the physical aspects and programme quality require managerial attention. For the hospitability sector (study B), it is service commitment, interaction quality and internal sense of happiness. Whereas for higher education (study C), it is administrative quality as well as the element of transformative quality, namely the university’s role in adding to its students’ emotional stability, which needs the attention of the top management.

This study provides researchers and practitioners with a roadmap for applying PLS-SEM and IPMA for continuous service quality improvement. The roadmap extends upon Ringle and Sarstedt’s (2016) work. It highlights critical decisions that need to be considered in the pre-analytical stages of the IPMA application, i.e. at the research design phase in selecting the most appropriate service quality measurement model specifications. It not only contributes to the existing body of knowledge by providing empirical evidence to advance theory development in the quality management field but also has implications for the practitioners in any service sector on where to focus their attention for an effective service improvement.