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Relying on Social Identity Theory (SIT), Relative Deprivation Theory (RDT) and System Justification Theory (SJT), this study aims at examining identity enhancement strategies of blue-collar workers who might be described as members of low-status groups having negative social identity. In the scope of this study, individual and collective strategies for identity enhancement of blue-collar workers have been proposed with the support of above mentioned theories. First of all, factors determining identity enhancement strategies have been described. Then, individual mobility conditions were explained and informal workplace learning was suggested as an individual mobility strategy for blue-collar workers to enhance social identity. In addition, it was argued that high self-monitoring blue collars are more likely than low self-monitoring blue collars to use individual mobility strategy. It was also emphasized that through union membership, high identifier blue collars will adopt a collective identity enhancement strategy. Finally, acceptance of low-status strategy was proposed for blue-collar workers in case they perceive their group’s low status as stable and legitimate.

This study aims to examine and compare the influence of the disposition to engage in engagement behaviors on physical and virtual engagement platforms, as well as the influence of these engagement behaviors on brand loyalty, value-in-use and word-of-mouth.

Data were collected using a survey distributed to a random sample of 10,000 fans of five teams in the Swedish top-division of elite football. An exploratory factor analysis was performed to derive a distinction between prevalent platforms, scales were validated through a confirmatory factor analysis and structural equation modeling was used to test the research model.

Customer disposition to engage with the sports team had a significant influence on customer engagement behaviors on both physical and virtual engagement platforms. However, engagement behaviors on virtual platforms were found to be more important than engagement behaviors on physical platforms for fostering brand loyalty and value-in-use.

The results highlight the importance of engagement behaviors with a brand on virtual engagement platforms. Thus, brand managers should prioritize their presence on social media to generate the positive outcomes of customer engagement behaviors.

By examining the effects of customer engagement behaviors on both physical and virtual engagement platforms, this study provides new insights to the emerging customer engagement literature.

The paper aims at assessing the role of the different stages of the employment process in gauging workers' willingness to upskill themselves at the end of a seasonal employment contract by investing in further training.

The paper analyses data from a dedicated survey administered to a sample of seasonal employees. Through a regression analysis it explores the different stages of the employment process (job search, selection on the job activities), making a distinction between monetary and nonmonetary components of the investment in training.

Results show that all stages matter, but they do not have the same importance. Ex-ante motivations and work experience, notably the level of perceived workload and organizational commitment, are the main factors affecting workers' willingness to acquire industry-specific skills through training.

So far, the literature has extensively dealt with the poor levels of training in seasonal employers, but it did not analyse worker’s willingness to invest in training over the different stages of the worker experience. This paper fills this gap by separately testing the relative importance of such stages and identifying the most important phases of the employment process.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

The appraisal of corporate reputation based on third-party corporate social responsibility (CSR) indices appears to have been institutionalized. The endorsement of such an approach by sustainability custodians and influencers undermines the uptake of the morality and legitimacy of CSR. This study takes a social realist perspective, which suggests that social phenomena such as CSR and corporate reputation are shaped by social structures and power relations. This study aims to contribute to a deeper understanding of the complex relationship between CSR and corporate reputation and understand ways in which the constructs are influenced by cognitive factors.

This study surveyed 411 respondents across five shopping malls and analyzed the data using path analysis of the structural equation modeling (SEM) technique. The mall-intercept survey sought to critically assess expectations of CSR vis-à-vis evaluation of corporate reputation. Based on a case study of three Johannesburg Stock Exchange listed companies, CSR expectations were measured along the philanthropic, economic, ethical and legal dimensions, while evaluation of corporate reputation was based on product quality, financial performance and social responsibility. SEM path analysis was used to extrapolate the predictive outcomes of CSR on corporate reputation.

Reputation for product quality and social responsibility is underpinned by the fulfillment of ethical CSR expectations, while philanthropic gestures enhance the evaluation of financial performance. Legal CSR significantly influences the reputation for social responsibility and product quality. Fulfillment of economic CSR expectations influences the reputation for product quality. However, no relationship was established between economic performance and social responsibility. Involvement in economic, philanthropic and particularly, legal CSR, are not indicative of the reputation for financial performance. Conversely, companies’ involvement in economic CSR does not suggest a higher propensity for social responsibility.

The predictive outcomes of CSR expectations on corporate reputation can reveal situated understanding of actual perceptions of corporate behavior.

Ethical business conduct is synonymously associated with social responsibility while espoused corporate philanthropy signals strong financial performance. The awareness of consumers’ cognitive evaluation of corporate reputation can offer a pathway to corporate communication professionals, policy makers and agencies to rethink and reposition CSR efforts.

Insensitivity to taken-for-granted cultural prescriptions and reliance on market-based reputational rankings undermine mutually beneficial stakeholder relationships and the social license to operate.

This study brings to the fore, cognitively dominated indicators of consumers’ perceptions of the reputation for CSR, to foster nuanced and halo-removed approaches to social responsibility. The authors show for the first time how companies’ skewed focus on corporate philanthropic giving paradoxically signals a capitalistic notion of social responsibility and unethical business conduct. This study offers a halo-removed orientation to the appraisal of CSR and corporate reputation.

This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.