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Due to the environmental concerns in our society, governments are moving towards green purchasing. However, public sector organizations have substantial internal problems. By using a theory of natural resource-based view, this study aimed to analyse the influence of leadership styles and innovation capabilities on green purchasing in the public sector organizations of a developing economy.

Data was collected from 199 purchasing professionals of public sector organizations, and hypotheses were tested through a quantitative method using partial least square-structural equation modelling with the help of SmartPLS version 4 to validate the measurement model.

This study identified that transformational leadership and delegation style of leadership have a significant and positive effect on innovation capability and green purchasing. Similarly, innovation capability mediates the relationship between leadership styles and green purchasing. However, transformational leadership found a more substantial effect on innovation capability and green purchasing than the delegation leadership style.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, addressing the important issues of how leadership styles and innovative capabilities (IC) can improve green culture, specifically green purchasing, to enhance ecological sustainability.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, it addresses how leadership styles and IC can improve green culture, specifically green purchasing, to enhance ecological sustainability.

This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.

The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.

The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.

This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.

This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.

Food service establishments and online food delivery companies use a revenue share model based on a commission rate. Because of the asymmetry of bargaining power, many food service establishments are vulnerable to a high commission rate. What is missing in the ongoing discussion about the revenue share model is the perspective of food consumers, who are the third party in the multi-sided market.

Within a willingness-to-pay (WTP) framework, we study if food consumers have preferences for the commission rate charged by food delivery companies to food service establishments. With 456 random consumers in the United States, we conduct a controlled experiment in which information is used as treatment in two groups. In the first group, the provided information only relates to the revenue share model (i.e. economic). In the second group, participants also received information about price control initiatives (i.e. economic and political).

Based on WTP-space mixed logit model results, there is a significant effect of information on preferences for the commission rate. While participants in the control group exhibited no aversion to the commission rate, participants who received treatment had a significant and negative WTP. The magnitude of the effect is estimated at -$1.08 for participants in the first treatment and -$2.28 for participants in the second treatment.

To date there is no applied research on the preferences of consumers in the online food order and delivery industry with respect to upstream conditions (i.e. commission rates).

The rapid expansion of internet usage and device connectivity has underscored the importance of understanding the public’s cyber behavior and knowledge. Despite this, there is little research that examines the public’s objective knowledge of secure information security practices. The purpose of this study is to examine how objective cyber awareness is distributed throughout society.

This study draws on a large national survey of adults to examine the relationship between individual factors – such as demographic attributes and socioeconomic resources – and information security awareness. The study estimates several statistical models using weighted logistic regression to model objective information security awareness.

The results indicate that socioeconomic resources such as income and education have a significant effect on individuals’ information security awareness with richer and more highly educated individuals exhibiting greater awareness of important security practices and tools. Additionally, age and gender represent consistent and clear informational gaps in society as older individuals and females are significantly less knowledgeable about an array of information security practices than younger individuals and males, respectively.

The findings have important implications for our understanding of information security behavior and user vulnerability in an increasingly digital and connected society. Despite the growing importance of cybersecurity for all individuals in nearly all domains of daily life, there is substantial inequality in awareness about secure cyber practices and the tools and techniques used to protect one’s self from attacks. While digital technology will continue to permeate many aspects of daily life – from financial transactions to health services to social interactions – the findings here indicate that some users may be far more exposed and vulnerable to attack than others.

This study contributes to our understanding of general user information security awareness using a large survey and statistical models to generalize about the public’s information security awareness across multiple domains and stimulates future research on public knowledge of information security. The findings indicate that some users may be far more exposed and vulnerable to attack than others. Despite the growing importance of cybersecurity for all individuals in nearly all domains of daily life, there is substantial inequality in awareness about secure cyber practices and the tools and techniques used to protect one’s self from attacks.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This paper aims to explore the relationship between market pricing and design quality within the development industry. Currently, there is a lack of research that examines real estate at the property level. Development quality is widely believed to have diminished over the past decades, while many investors seem uninterested in the design process. The study aims to address these issues through a pricing model that integrates design attributes. It is hoped that empirical findings will invite broader stakeholder interest in the design process.

The research establishes a framework for assessing spatial compliance across residential developments within London. Compliance is assessed across ten boroughs, with technical space guidelines used as a proxy for design quality. Transaction prices and spatial assessments are aligned within a hedonic pricing model. Empirical findings are used to establish whether undermining spatial standards presents a significant development risk.

Findings suggest a relationship between sale time and unit size, with “compliant” units typically transacting earlier than “non-compliant” units. Almost half of the 1,600 apartments surveyed appear to undermine technical guidelines.

It is suggested that an array of design attributes be explored that extend beyond unit size. Additionally, future studies may consider the long-term implications of design quality via secondary transaction prices.

Practical implications include the development of a more scientific approach to design valuation. This may enhance the position of product design management within the development industry and architectural services.

Social implications may include improvement in residential design.

An innovative approach combines a thorough understanding of both design and economic principles.

The purpose of this paper is to analyze the impact of the coronavirus (COVID-19) pandemic on participation and time allocated to work from home (WFH) by ethnic/racial group.

The authors employ USA time-use data [American Time Use Survey (ATUS)] for the 2017–2020 period and a parametric approach in their analysis.

Estimates show that the time allocated to WFH increased during COVID-19, especially for women. This increase is likely driven by more workers shifting to WFH (higher participation) rather than by longer hours worked by those who already teleworked. The authors also find relevant differences in the impact of COVID-19 on WFH by ethnic/racial group. Among ethnic/racial groups, only Asians increased WFH compared to White Americans. Within this ethnic group, the authors find significant differences across genders. Asian men increased participation in WFH, whereas Asian women increased both participation and hours worked, compared to White American women. Differences in this racial/ethnic group could be explained by previous research, which demonstrates a higher ability of Asians to perform job tasks remotely. However, this finding could also be attributed to an increase in discrimination during the COVID-19 pandemic.

This paper contributes to the recent and limited literature exploring the heterogeneous impact of COVID-19 on participation and time allocated to WFH by ethnic/racial group. Understanding the mechanisms driving vulnerable populations' abilities to work during socioeconomic downturns is of high policy importance.

This study responded to the call to empirically reconcile conflicting findings in unethical pro-organizational behavior (UPB) literature. It did so by examining the influence of organizational culture on the relationship between affective organizational commitment and UPB.

Using a sample of 710 U.S. service sector employees based on a three-wave data collection design, structural invariance assessment was utilized to evaluate the relationship between affective organizational commitment and UPB across organizational cultures with opposing effectiveness criteria (i.e. focused on stability vs flexibility).

The result indicated a statistically significant positive direct effect between affective organizational commitment and UPB for the stability-focused cultures, while finding a statistically insignificant effect for the flexibility-focused cultures. These results support organizational culture research, which shows that organizational cultures with opposing effectiveness criteria (i.e. stability vs flexibility) can either encourage or discourage ethical behavior.

While leaders and managers encourage employee commitment to the organization, it is important to understand that increased organizational commitment is not limited to positive outcomes. Cultivating elements of flexibility-oriented cultures, like promoting teamwork (as in clan cultures) or fostering innovation and adaptability (as in adhocracy cultures), can be a strategic approach to minimize the chances of UPB among committed employees.

By integrating insights from social exchange theory, Trevino’s interactionist model and the competing values framework, we have contributed to a nuanced understanding of how different organizational cultures can suppress or stimulate UPB.

This study aims to examine the connection between scholars' research performance and the multidisciplinary nature of their collaborative research. Furthermore, in response to mixed results regarding the effects of multidisciplinarity on research performance, this study explores how human resource management (HRM) practices may moderate this link.

The authors built a model based on the theoretical arguments and empirical evidence found in the review of diversity and HRM literature. The authors also performed a quantitative study based on a sample of scholars in the field of management. Different econometric estimations were used to test the proposed model.

The results of this empirical analysis suggest that multidisciplinary research has a non-linear effect on research performance. Certain HRM practices, such as development and collaboration, moderated the curvilinear relationship between multidisciplinarity and performance, displacing the optimum to allow higher performance at higher levels of multidisciplinary research.

The paper provides advances on previous works studying the curvilinear relationship between multidisciplinarity and the researchers' performance, confirming that multidisciplinarity is beneficial up to a threshold beyond which these benefits are attenuated. In addition, the findings shed light on important issues related to team-oriented HRM practices associated with the outcomes of multidisciplinary research.

The purpose of this paper is to identify the practices that owners of public profiles in social networking sites can leverage to actively build online reputation and to evaluate the impact of the adoption of such practices on the initial formation of trust toward these individuals when they are presented as new virtual work partners.

A theoretical model was developed and an experiment with 233 participants was utilized to assess the model using partial least squares structural equation modeling.

The results suggest that individuals can build their online reputations in public profiles of social networking sites via a series of practices of self-disclosure of information and that the adoption of these practices has significant effects on the initial formation of trust toward the profile owner in virtual work contexts. Categorization mechanisms such as stereotyping, unit grouping and reputation categorization have been found to contribute to the initial formation of trust, both from an affect and cognition-based perspectives.

Little is known about the information disclosure practices in public profiles of social networking sites that new work partners can adopt to facilitate the formation of trust between them before they start working together. This study has contributed to the existing body of literature by clarifying these practices and the relative importance of online reputation to the initial formation of trust during the outset of a new virtual work relationship.