Search results

The major purpose of this research article is to empirically analyze a moderated-mediated model to comprehend the interrelationships between religiosity, life hardship, attitude toward social entrepreneurship (SE) and corporate social entrepreneurial orientation (SEO).

The constructivist grounded theory method was used to analyze interviews, and partial least squares structural equation modeling was selected to analyze the developed nine hypotheses.

Based on the structural model outcomes, the practicing religious believers reported a significantly higher level of corporate SEO and propensity for social proactiveness, innovativeness, risk-taking, socialness and persistence (dimensions of SEO) than the nonpracticing believers.

This study provides the practical implication that social entrepreneurs with a higher degree of congruence with the prevailing religious institutionalized logic in a society have a higher inclination to create social value through corporate practices and operations.

This study presents an SEO scale that incorporates the dimensions of two SEO scales developed by Kraus et al. (2017) and Syrjä et al. (2019). To the best of the author’s knowledge, the applicability and generalizability of this scale were supported for the first time in the SE discipline, particularly tourism SE. This scale effectively captures more characteristics of SE, particularly in the face of inefficient political and institutional forms.

By adopting a cultural lens, this study aims to conceptualize destination-community hospitality to capture societal hospitality at the destination as an intangible asset. Destination-community hospitality comprises a set of attitudes and traits that are organically conveyed by community members and directly experienced by tourists. The paper contributes to efforts aimed at freeing hospitality from the confines of commercial lodging and food and beverage establishments.

This study proposes an affection–attention–awareness (AAA) framework by drawing on the pertinent literature and leveraging the affective–behavioral–cognitive model of attitudinal change. It focuses on the effects of cognition in conceptualizing destination-community hospitality as the core of the framework. Methodologically, the framework is illustrated with qualitative data including observational fieldwork and interviews conducted in Iran.

Illustration of the AAA framework in the context of Iran highlights how welcoming attitudes are leveraged at a destination as an ingrained community mindset even in the absence of formal initiatives or professional training. It underscores the hospitality advocacy role of local-community members irrespective of public-sector policy and capacity deficiencies.

Destinations that strive to attract tourists should tap into the significant wealth of intuitive hospitality within communities as an intangible resource. The ingenuity should be preserved to sustainably enhance the overall tourist experiences. The framework can serve as a guide to strategically facilitate destination-community hospitality.

Research on community-wide hospitality at destinations, as a major cultural asset in the context of strategic hospitality management, remains underdeveloped. With illustrative evidence, the findings elevate the critical role of community members as innate advocates of hospitality in developing destinations. The proposed framework of destination-community hospitality provides a new perspective and impetus for investigating hospitality beyond commercial domains.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.

This study aims at determining the influence of the competitive strategy types and organizational structure dimensions on Cost of Quality (CoQ) in Food and Beverage (F&B) small- and medium-sized enterprises (SMEs).

A survey questionnaire was sent to F&B companies in Greece and 307 responded positively and fully completed the questionnaire. The research model developed (consisting of the competitive strategy types, the organizational structure dimensions and CoQ) was tested using the exploratory and confirmatory factor analyses and the structural equation modeling (SEM) technique.

The findings indicated that cost leadership, centralization and formalization influence the CoQ positively and significantly. By contrast, differentiation does not influence CoQ.

The small sample of the responding companies operating in one country, the different F&B sub-sectors, the subjective perceptions of only one representative per company and the cross-sectional nature of the study are the main limitations of the present study.

This paper provides academicians and practitioners with a better understanding of the factors that influence the quality-cost level.

To the best of the authors' knowledge, this is the first study that examines the effect of competitive strategy and organizational structure on CoQ.

Within a framework of supply chain (SC) coordination, this paper analyzes a green SC consisting of a retailer and a manufacturer, under government incentives and legislations and the consumer environmental awareness. To mitigate carbon emissions and promote the sustainability of the SC, a customized carbon emission trading mechanism is developed.

A game-theoretical decision model formulated determines the optimal sustainability level and the optimal quota of carbon credit from the ceiling capacity set by the government. In order to coordinate the SC and optimize environmental decisions, a novel combination of consignment and zero wholesale price contracts is proposed.

Analytical and numerical analyses conducted highlight that the proposed contract generates a Pareto improvement for both channel members, boosts the profit of the green SC, enhances the sustainability level of the channel and contributes to a reduction in the requested carbon emission credit by the manufacturer.

With the proposed mechanism, governments can protect their industries and, more importantly, comply with European Union (EU) rules on annually reducing emission ceilings allocated to industries.

Different from previous studies on cap-and-trade strategies, the proposed mechanism enables companies to select lower emission quota/allowances than the maximum amount set by the government, and in return, companies can benefit from several incentive strategies of the government.

Finding an appropriate place for temporary housing after an earthquake is one of the main challenges of disaster risk management, especially in developing countries. Therefore, it is necessary to create pre-disaster location plans for the homeless population. This study aims to systematically find safe places and select suitable sites according to influential factors.

The research methodology used is a descriptive–analytical method. A field survey with a quantitative–qualitative approach is applied to recognize physical vulnerabilities and select suitable sites for temporary settlements. Due to the occurrence of several earthquakes in recent decades around the city of Isfahan, Iran, this area has been studied. Fuzzy analytic hierarchy process, geographic information system and rapid visual screening have been used for data analysis.

According to the site selection and vulnerability criteria and their prioritization, the findings indicate that 60% of the study area is vulnerable. Moreover, vacant lots, stadiums and public green spaces that can be used as multi-purpose sites are the most appropriate options for the temporary settlement.

The research criteria are generalizable and can be used for decision-making, concerning urban fabric vulnerability and site selection of temporary housing in cities exposed to earthquake risk.

Cultural features, accessibility, land conditions, the slope and type of land, availability and construction materials were addressed in locating temporary settlements. In addition to vacant lots and open spaces, safe buildings were also identified for temporary housing, and religious minorities and similar communities were considered.

The purpose of this study is to discover the components of virtual leadership in universities and higher education institutions during Covid-19 pandemic.

This research uses the qualitative research design, and semi-structured interviews with senior leaders were conducted with non-random purposeful and snowball sampling methods. Also, grounded theory was used for analyzing, coding and classifying the data.

After analyzing data, five main components influencing virtual leadership including leader's personality traits, followers' characteristics, technological, environmental and organizational components were identified.

As leadership, particularly virtual leadership, highly depends on context such as the level of technology in that certain region, the results cannot be generalized to other sectors or countries.

The research advances leadership development theory by highlighting the main components of virtual leadership in educational sector as a comprehensive perspective and complement the other aspects of virtual leadership such as consequences and challenges investigated by other studies.