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This study aims to identify how ICT appeared as an emergent business strategy and to investigate the impact of ICT adoption factors on the perceived benefits of micro, small and medium enterprises (MSMEs).

A total of 393 responses from Indian small and mid-size enterprises (SMEs) were collected for the final analysis. The study presents the partial least-squares structural equation modeling with the Chi-square test and descriptive analysis as a methodology based on numerous independent variables and one dependent variable.

The findings indicate that ICT adoption during and following the COVID-19 pandemic is constant in nature of the enterprise. Moreover, the results indicate that different adoption of ICT factors influence on perceived benefits of organizational performance of Indian MSMEs that lent good support except for the regulatory framework.

The implications of the current research help Indian MSMEs to take investment decisions in various technologies that help the organization. Furthermore, managers and practitioners help the organization in deciding which technology adoption factors are more critical to the betterment of the organization.

The study found certain ICT adoption factors that have a significant role in organizational performance in Indian MSMEs. Moreover, during COVID-19, investigate ICTs' role as a business strategy.

Rural communities around the world are searching for solutions to upkeep, restore and improve local services that are deteriorating. They are exploring the potential of a digital transition along with the opportunities and threats created by new patterns of mobility and closer links with urban areas. The expansion of information and communication technologies (ICT)-enhanced applications enables rural communities to improve their quality of life. The concept of smart village is primarily about how rural communities make the best use of both ICT and social innovation by responding to the ongoing and emerging challenges. Therefore, the aim of this paper is to investigate strategies for adoption of smart villages along with the challenges faced.

A quantitative research methodology was adopted in this research. A web-based questionnaire survey was conducted to collect data. In total, 110 fully completed and useable questionnaires were received. Statistical analyses were undertaken using the Statistical Package for Social Sciences (SPSS).

The results indicate that lack of budget, lack of clear strategies for development of sustainable “smart villages”, lack of collaboration between stakeholders and lack of knowledge related to “smart villages” are the most debated challenges for implementing smart village agenda. Whereas smart energy, smart healthcare, smart transport, smart education and smart water are the top five most important smart village strategies.

Despite the novel insights provided by this study, it has some limitations. Given that the research reported in this paper is based on literature review and small-scale survey, results presented are only tentative and not generalisable. The findings of this paper are limited to the UK context only. Although generalisability outside of this context may be limited, the authors infer that the results are relevant to other comparable developed countries.

Research on smart village development is rare. This paper presents a theoretical basis on the concept of smart villages. It adds to the rich insight that goes into the understanding and awareness of the current smart village strategies along with the key challenges organisations encounter when implementing smart village initiatives. This research has implications towards informing professionals and policymakers on key lessons learnt during the implementation of smart village strategies. Also, this paper contributes to the academic debate on smart village development and provides useful recommendations to both policymakers and practitioners.

In this chapter, four bi-objective vehicle routing problems are considered. Weighted-sum approach optimization models are formulated with the use of mixed-integer programming. In presented optimization models, maximization of capacity of truck versus minimization of utilization of fuel, carbon emission, and production of noise are taken into account. The problems deal with real data for green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country, and La Rioja, Spain.

Heterogeneous fleet of trucks is considered. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Modern logistic companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, and utilization of fuel, carbon emission, and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution. The computational experiments were performed using the AMPL programming language and the CPLEX solver.

The purpose of this paper is to examine how managers react to sexual harassment as a function of the harasser role that includes a customer as a source of harassment and an organization’s climate for sexual harassment.

Using an experiment with a 2 (harasser role: coworker or customer) × 2 (organizational climate of sexual harassment: tolerates or does not tolerate) between-subjects design, 162 hotel managers were randomly assigned to read one of four conditions.

Both the harasser role and organization’s climate for sexual harassment influenced the managers’ sexual harassment reactions, specifically whether they label the incident as sexual harassment and attribute responsibility to the organization. The managers’ gender was found to moderate these relationships.

The results underscore the importance of understanding reactions to sexual harassment because, regardless of who harasses (coworker or customer) and the organizational climate (tolerates or does not tolerate sexual harassment), sexual harassment of any form can be harmful for the well-being of hospitality employees. These results also provide educational implications.

This is the first known experimental study to examine how hospitality managers react to sexual harassment when the harasser role includes a customer versus a coworker. The results illustrate that the same sexually harassing behavior was perceived less negatively – in regard to both the labeling and attribution of organizational responsibility – when it was done by a customer than by a coworker.

The purpose of this paper is to examine the non-linear aspects of the asymmetry-performance relationship under varying conditions of trust and innovation. Its novel approach is useful for addressing the strategic elements of supply chain management (SCM) relationships based on trust and innovation decisions.

Results are based on a study of 90 managers from small- and medium-sized firms in Spain. Instead of a classical linear relationship analysis, the authors performed a non-linear analysis, using polynomial modeling and Warp 3 partial least squares method, which provides a more nuanced view of the data and constitutes an original approach to empirical research in SCM.

This study adds a new viewpoint on SC relationships by suggesting that not all trust and innovation development leads directly to performance improvement. The principal finding is, in varying trust and innovation contexts, that the influences of asymmetry on performance have uneven characteristics and follow non-linear paths.

This study focuses on only one particular institutional environment in one country. The data are also cross-sectional, which makes it difficult to empirically test causality.

The findings provide rational insights to managers on when it is appropriate to reduce (or not) asymmetric relationships with partners.

Trust and innovation are important and ones of the key requirements of supply chain relationships in any environment, this study argues that the interactions of key SCM elements that drive members to better performance are more complex and non-linear.

This paper aims to examine the non-linear aspects of the relationship between asymmetry and performance in supply chains (SCs), under varying intensities of collaboration and integration.

The paper offers a useful new approach to designing strategic elements of supply chain management (SCM) relationships. Using the partial least squares method, an empirical study of 66 companies in Spain has been conducted to clarify contemporary relationships, suggest new directions and ultimately contribute toward developing SCM theory.

The influences of asymmetry on performance in varying collaboration and integration contexts are shown to be unstable and have non-linear paths. It is inappropriate for all firms to collaborate or integrate continually, even for a prescribed period. Furthermore, due to asymmetry, SCM processes are more complex.

The results’ validity may be limited to contexts specific to Spanish SCs. It would be valuable to investigate the impact of asymmetry on firms’ performance and relationships in other markets.

Collaborations and integration between partners in a SC might change the role of asymmetry from restraining to improving performance. The best way to improve performance in asymmetric relationships is to collaborate. Certain dimensions of integration and full integration are not necessarily required to improve firms’ performance under asymmetry conditions.

The study adds a new viewpoint on SCM by suggesting that not all collaboration and integration developments lead directly to improved performance.

Impedance data obtained by electrochemical impedance spectroscopy (EIS) are fitted to a relevant electrical equivalent circuit to evaluate parameters directly related to the resistance and the durability of metal–coating systems. The purpose of this study is to present a novel and more efficient computational strategy for the modelling of EIS measurements using the Differential Evolution paradigm.

An alternative method to non-linear regression algorithms for the analysis of measured data in terms of equivalent circuit parameters is provided by evolutionary algorithms, particularly the Differential Evolution (DE) algorithms (standard DE and a representative of the self-adaptive DE paradigm were used).

The results obtained with DE algorithms were compared with those yielding from commercial fitting software, achieving a more accurate solution, and a better parameter identification, in all the cases treated. Further, an enhanced fitting power for the modelling of metal–coating systems was obtained.

The great potential of the developed tool has been demonstrated in the analysis of the evolution of EIS spectra due to progressive degradation of metal–coating systems. Open codes of the different differential algorithms used are included, and also, examples tackled in the document are open. It allows the complete use, or improvement, of the developed tool by researchers.

Resilience, the ability of start-ups to deal with anticipated instabilities and probable disruptions, is becoming an important success element during coronavirus disease 2019 (Covid-19). To survive in this pandemic situation, resilience is an important concept for start-ups. The present paper aims to “identify”, “analyse” and “categorize” the resilience factors for start-ups during the Covid-19 pandemic using total interpretive structural modelling (TISM).

The resilience elements of start-ups during Covid-19 were identified and shortlisted during the first phase, which included literature analysis and extensive interaction with experts. TISM was used in the second phase to investigate or to determine how the factors interplayed between the resilience factors of start-ups during Covid-19. The Matrice d'impacts Croises Multiplication Appliquee a un Classment (MICMAC) method is used to rank and categorize the factors. Closed-ended questionnaire with the scheduled interview was conducted to collect the data.

The first part of the study found ten resilience elements in total. The TISM digraph was constructed in the second step to show why one resilience component led to another. The MICMAC analysis divided these factors into four groups: autonomous, linkage, dependent and independent. These groups represented resilience variables based on their driving and dependent power, which assist executives and managers in proactively addressing them while using the TISM digraph as a guide.

During the Covid-19 epidemic, this study focused primarily on resilience characteristics for Indian start-ups.

This study will help key stakeholders and scholars to better understand the elements that contribute to start-up's resilience.

The TISM method for start-up's resilience is suggested in this paper, which is a novel attempt in the field of resilience in this industry.

Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing architectures in order to create knowledge‐rich environments populated by interconnected smart devices. In this paper we point out some problems of these previous initiatives and introduce SoaM (Smart Objects Awareness and Adaptation Model), an architecture for designing and seamlessly deploying web‐powered context‐aware semantic gadgets. Implementation and evaluation details of SoaM are also provided in order to identify future research challenges.