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Built upon customer engagement marketing theory and uses and gratification theory, this study examines the link between individual social media marketing (SMM) performance indicators and restaurant sales performance at the firm level. Moreover, the study investigates the moderating effect of advertising expenditure on this proposed relationship.

Random effect regression models were developed in Stata to examine the associations between SMM performance indicators, advertising expenditure, and restaurant firm revenue. Twelve years of SMM data from brands' Facebook pages were collected with a web scraper built in Python. Natural language processing was used to analyze the sentiment of user-generated content (UGC).

The results suggest that restaurant annual sales revenue increases as the volume of brand posts, “like”s, “share”s and positive comments on restaurants' Facebook pages increase. However, the total number of comments and the number of negative comments show non-significant associations with revenue. Firm advertising expenditure negatively moderates the relationships between sales revenue and the number of “like”s, “share”s, total comments and positive comments.

Restaurants benefit from making frequent posts on SNSs. Promotions that motivate online users to “like”, share, and comment on brand posts should be implemented. Firms with limited advertising budgets are encouraged to actively create buzz on SNSs due to evidenced stronger effects of UGC on sales performance than large advertisers.

This research bridges the gap by studying the effects of individual SMM performance indicators on restaurant financial outcomes. The findings support the effectiveness of SMM; and, for the first time, demonstrate that SMM could generate a more profound impact for firms with low advertising budgets.

The objective of the paper is to get a better understanding of capacity utilisation (CU) in Indian public bus companies. More specifically, this paper would be measuring CU and identifying the drivers of the same. Finally, the influence of CU on the financial performance of Indian bus companies is examined.

The study adopted data envelopment analysis (DEA) to measure the CU in Indian public bus companies. Truncated regression was used to identify the drivers of CU. Subsequently, the ordinary least squares (OLS) regression was used to analyse the influence of CU on Indian bus companies' financial performance. The period of study was from 2013 to 17.

The significant drivers of CU were fleet age, passenger lead and fleet utilisation. Additionally, it was found that CU had a significant positive influence on the financial performance of Indian public bus companies and a unit increase in unused capacity has led to an increase of 7% in the operating ratio of the bus companies.

Getting insights into CU, apart from technical efficiency, is of immense use to both public transport researchers and practitioners. Managers of public bus companies should be mindful of CU as it has a significant bearing on their financial performance.

This is the first study in public transport, which establishes the linkage between CU and financial performance. Besides, a modified measure of cost-efficiency has also been conceptualised in this study.

The purpose of this study is to disclose ontology of DSI as a novel concept in servitization community, explore the research context and themes (i.e. technological and industrial sectors) where DSI emerges, unveil methodological complexities of the research on digital servitization and DSI and provide guidelines for future research avenues regarding DSI.

Bearing in mind the relative novelty of DSI as a concept in servitization literature, the authors adopted a systematic literature review approach to identify 111 peer-reviewed articles published in English language and available in business and management disciplines via scholar databases (Scopus). The analysis of literature discloses descriptive and thematic insights regarding digital servitization and DSI.

The study provides valuable insights from the descriptive and thematic analyses where classification of articles per publication year, citations, methodology/type of the paper, geographical location of data collection, as well as industrial sector and technological contexts are discussed. Moreover, the unique value of this study is observed through its specific focus on the characteristics of DSI-related literature.

The study is among the first of its kind to provide extensive descriptive and thematic insights on the available literature dealing with digital servitization and DSI, mapping out prior research across a wide spectrum of publication outlets and illustrating the chronological evolution of research on digital servitization and DSI.

Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT).

This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA).

EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use.

The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive.

This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry.

This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.

The evolution of technology from the most recent industrial age to the technology era better known as Industry 4.0 resulted in greater demand for horizontal, vertical and end-to-end digital integration. Prior studies show that Industry 4.0 adoption majorly influences the sustainability aspects in a supply chain network. The purpose of this paper is to identify the Industry 4.0 enablers of supply chain sustainability and further attempt to propose a research framework to bridge the theoretical gaps.

In this research study, the authors have used a systematic literature review methodology in the field of Industry 4.0 and sustainable supply chain management. The list of papers was downloaded from Scopus (www.scopus.com) database. Through strict screening, only journal papers were selected for conducting the review of the literature.

The review brings out some interesting findings which will be helpful for the research community. There have been limited research in the area of managing supply chain network sustainability through Industry 4.0 technologies. The authors found only 10 papers out of a total of 53 papers which emphasize on smart manufacturing, smart production system, smart warehouse management system, smart logistics and sustainability. Most of the previous research studies have ignored the social aspects of supply chain sustainability. Finally, the authors identified 13 key enablers of Industry 4.0 playing an important role in driving supply chain sustainability.

The strategies for Industry 4.0 should be refined and detailed to develop economic and social systems that can act flexibly to sudden changes in the system. Top management must be convinced for prioritizing investment support and creating a system that can facilitate technology convergence. Managers must also act on new models of employment and frame plans to continuously improve the system. In addition, managers must focus on establishing a collaborative platform to facilitate high-tech research and developments. Finally, it is essential to develop a performance management system for monitoring all actions in the supply chain network.

Integrating two independent subjects is the uniqueness of the current study. Here, Industry 4.0 and supply chain sustainability have been integrated to build the research framework, and in such a process, the authors have extended the existing knowledge base.

The alignment of procurement strategy with overall business strategy is important for superior firm performance. It is also essential for firms’ purchasing structure to fit the purchasing strategy whether it is cost reduction; value analysis and/or improving delivery and increasing flexibility for achieving superior purchasing performance. The purpose of this paper is to scientifically examine the influence of organization culture (OC), green supplier development (GSD), supplier relationship management, flexibility and innovation on sustainability in supply network (SSN) under the moderation effect of institutional pressures and resources availability.

The study is grounded by integrating institutional theory (IT) and resource-based view (RBV) theory. The study empirically tests the conceptual model through survey data gathered from 175 respondents in the KwaZulu-Natal province of Southern Africa using structural equation modeling which is a multivariate data analysis technique that permits to simultaneously examine many relationships among manifest and latent variables.

It was found that OC plays a crucial role in shaping the workforce behavior and responsible for enhancing GSDs and building good relationship with suppliers which ultimately results into increased flexibility and innovativeness. Coercive pressures (CPs) play a moderating role between the causal relationship of innovation and SSN. Therefore, CPs have got the ability to amplify or reverse the effect between innovation and SSNs.

The study suffers from few limitations. First, the study is restricted to one particular province in South Africa. Second, cross-sectional data were used for testing of model in the research study.

The findings are of great importance for both the researchers and supply chain practitioners. Supply chain practitioners may use this knowledge for benchmarking the supply network configuration process and continuously improve the process. The tested model actually shows the mechanism for enhancing SSNs. In today’s dynamic and uncertain business environment, all firms in the supply network aims to minimize risks and maximize profitability. The findings show that CPs play a moderating effect on the relationship between innovation and SSN. Whenever government authorities and institutions pressurize firms for minimizing pollution levels, we see a trend of increased innovations in the form of new product developments, usage of eco-friendly raw material and application of eco-friendly technology which ultimately minimizes the carbon footprint. Through such initiatives steel and engineering firms conform to the government norms and regulations. However, innovations are possible through collaboration with specialist suppliers and sub-suppliers by adopting a common standard across the supply network. Through this overall process of innovation, the focal firm and sub-suppliers linked in the network will benefit and ultimately achieve a competitive edge. Therefore, firms can experience multiple benefits in terms of lower development costs, lower project cycle completion time, improvement in design for re-manufacturability, low downtime, low supply risks, reduction of greenhouse gas emissions and, ultimately, sustainable development.

The study is unique from dual perspective – both in terms of scope and contribution to supply chain management literature. First, the study integrates flexibility and innovation to study the impact on SSNs. Second, it integrates both IT and RBV theory of firm to test the moderation effect and the findings further opens up window for future research.

This paper aims to examine the link between information systems (IS) agility, HR performance management systems and job satisfaction using organizational information processing theory. The objective of this study answers the following questions: How does use of different IS agility impact HR systems and job satisfaction? What are the connecting pathways by which IS agility affects HR systems and job satisfaction?

The authors developed a theoretical framework based on the organizational information processing theory and collected primary data through an online-based questionnaire. Following these procedures, the authors analyzed the data using structural equation modeling (SEM).

SEM analysis of the data from 150 respondents supports the organizational information processing theory. The authors proposed eight hypotheses, and only one was rejected.

The data were collected from South Africa only, which is an emerging economy, and these cross-sectional data were gathered from the perspectives of the respondents.

The present paper empirically tests the conceptual model through the lens of organizational information processing theory.

COVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.

We adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.

An AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.

As the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.

Supply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.

The present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

This study aims to comprehend the application of analytics in the supply chain during the ongoing COVID-19 crisis and identify the emerging themes.

The author downloaded a list of research articles on the application of analytics to the supply chain from SCOPUS, conducted a systematic literature review for exploratory analysis and proposed a framework. Notably, the author used the topic modeling technique to identify research themes published during the ongoing COVID-19 crisis and thereby underscore some future research directions.

The author found that artificial intelligence, machine learning, internet of thing and blockchain are trending topics. Additionally, the author identified five themes by topic modeling, including the theme “Social Media information in Supply chain.”

The results were derived from a data set extracted from SCOPUS. Thus, the author excluded all studies not listed in SCOPUS from the analysis. Future research with articles indexed in other databases should be investigated to get a more holistic perspective of specific themes.

This study provides a deeper understanding and proposes a framework for applications of analytics in the supply chain that researchers could use for future research and industry practitioners to implement in their organizations to make a more sustainable and resilient supply chain.

This study provides exploratory information from published articles on the use of analytics in the supply chain during the COVID-19 crisis and generates themes that help understand the emerging and underpinned area of research.