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The purpose of this paper is to provide a comprehensive review on the academic journey of artificial intelligence (AI) in agriculture and to highlight the challenges and opportunities in adopting AI-based advancement in agricultural systems and processes.

The authors conducted a bibliometric analysis of the extant literature on AI in agriculture to understand the status of development in this domain. Further, the authors proposed a framework based on two popular theories, namely, diffusion of innovation (DOI) and the unified theory of acceptance and use of technology (UTAUT), to identify the factors influencing the adoption of AI in agriculture.

Four factors were identified, i.e. institutional factors, market factors, technology factors and stakeholder perception, which influence adopting AI in agriculture. Further, the authors indicated challenges under environmental, operational, technological, economical and social categories with opportunities in this area of research and business.

The proposed conceptual model needs empirical validation across countries or states to understand the effectiveness and relevance.

Practitioners and researchers can use these inputs to develop technology and business solutions with specific design elements to gain benefit of this technology at larger scale for increasing agriculture production.

This paper brings new developed methods and practices in agriculture for betterment of society.

This paper provides a comprehensive review of extant literature and presents a theoretical framework for researchers to further examine the interaction of independent variables responsible for adoption of AI in agriculture.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2020-0448

A food delivery app (FDA) is a technological advancement connecting restaurants and consumers, making it possible to deliver food home conveniently. The current study seeks to identify the factors affecting consumers' continuance intention and sharing intention toward the FDA in the USA and Canada using an integrated framework built using trust transfer theory and a variety of constructs.

The authors collected data/inputs from 476 respondents in the USA and Canada who had used FDAs in the past and analyzed them using the structural equation modeling technique.

The results indicate that trust in FDA, trust in the user community and commitment affect continuance intention and sharing intention. Interestingly, trust in the seller does not influence commitment, continuance intention and sharing intention. Additionally, the trust disposition and reputation of the FDA play an important role in building trust in FDA.

The present study combines the trust transfer theory with various important constructs such as commitment, trust disposition and reputation of the FDA to build an integrated framework to elucidate the continuance intention and sharing intention toward FDAs.

This study facilitates the FDA providers to understand how trust disposition, the reputation of the FDA and trust in the Internet build trust among FDA consumers. The study also helps them to fine-tune their trust-building strategy by considering several trust targets. It further enables them to appreciate how commitment results in continuance intention and sharing intention toward FDA.

It is an original study investigating the role of various constructs and trust transfer theory in shaping the consumers' continuance intention and sharing intention toward the FDA.

This study aims to examine the factors (Stimuli) enhancing perceived utilitarian, social and conditional values (Organisms) of social commerce (s-commerce) platforms and their impact on small and medium enterprises’ (SMEs’) behavioral intention (Response) to adopt s-commerce.

Survey data were gathered from 304 Indian SMEs using s-commerce platforms. Data were analyzed using SmartPLS 3 software.

The results indicated that perceived values significantly impact SMEs’ behavioral intention to adopt s-commerce. Among conditional, utilitarian and social values, the conditional value of s-commerce sites was found to be the strongest motivator for SMEs to adopt s-commerce.

This research contributes to the growing literature on s-commerce, explaining how perceived value influences the decision of SMEs to adopt s-commerce platforms.

Among the significant influencers, perceived usefulness and perceived reputation were found to be the most effective triggers that stimulate perceived values of s-commerce sites. The findings draw due attention from policymakers toward environmental cues such as the legal and regulatory environment, which are instrumental in creating the most important perceived value for SMEs, i.e. conditional value.

By employing the inputs from the theory of consumption values and the Stimulus-Organism-Response framework, this original study looked beyond the technology factors and examined the role of perceived values of s-commerce platforms in shaping SMEs’ behavioral intention to adopt.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.

The manufacturing industry is presently experiencing technological disruption on a global scale. Consequently, to tackle such disruption, firms are identifying a volatile, uncertain, complex and ambiguous (VUCA) scenario and seeking ways to counter it. Accordingly, this paper aims to investigate the employee performance through assessing organizational citizenship behaviour (OCB) among the shop floor employees of the fast-moving consumer goods (FMCG) industry where a high-performance work system (HPWS) has been implemented.

A descriptive research design was used in the study, and 395 shop floor employees working in leading multinational firms, with a minimum global turnover of US$1bn, were interviewed. These manufacturing firms were located in three industrial clusters in the northern part of India.

The results indicate that HPWS influences OCB. Most of the dimensions of HPWS and OCB were found to be positively associated. The findings also disprove the labour process theory in the context of the study.

The findings report a broad view of the relationship between HPWS and OCB in the Indian manufacturing context. The study offers the practical insights that HPWS is a universally accepted framework and that organizations should focus on the effective implementation of HPWS in a VUCA scenario, which is in line with past studies. The study also provides future directions for research.

This paper has established the relationship between HPWS and OCB in the manufacturing sector, especially for shop floor employees.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

Over the past few decades, many initiatives have been proposed in response to critical environmental challenges. However, in most cases, progress has been inadequate, raising questions as to why so few organisations have been successful in adopting effective sustainability measures. To address this dilemma, this paper aims to propose a range of sustainability-related co-opetitive strategies that are likely to be beneficial for organisations and society. The research findings provide support for co-opetitive approaches to corporate social responsibility (CSR) and sustainability by providing evidence within an Australian context.

Research methods comprised 14 interviews with senior executives/managers from private and public sector organisations in Australia. Thematic content analysis indicates the presence of three types of drivers (commonality-driven, competition-driven and collaboration-driven) and three critical success factors (governance, public policy and relationship principles) related to co-opetition, CSR and sustainability.

Findings indicate that inter-firm co-opetition could be considered a viable strategy to improve performance across the economic, social and environmental dimensions of sustainability. Limitations concern the number of interviews conducted.

Based on the research findings, a typology was created that depicts different forms of co-opetition in CSR/sustainability and their relationships with firm performance. Moreover, the typology illustrates the importance of co‐opetitive partnerships in supporting effective responses to sustainability challenges and opportunities.

The industry is relying on the preventive maintenance techniques that can minimize failures and provide industrial plants with effective equipment, but in many companies the maintenance tasks are performed very frequently and not as per plan and do not take into consideration the conditions of the plant and equipments. The failure of each and every component needs to be studied in order to choose the best maintenance strategy. This paper presents a fuzzy VIKOR (Multicriteria Optimization and Compromise Solution) technique which is used in developing a comprehensive approach for maintenance strategy selection in the Deinking plant of the paper industry to choose the appropriate maintenance strategy thereby reducing the unnecessary cost incurred on the maintenance.

In this paper, the Fuzzy VIKOR based methodology was applied for determining the maintenance criticality index of the deinking plant of the paper industry. The effect of failure of components were evaluated by three maintenance experts on five performance criteria that is chance of failure, chance of non-detection, downtime length, severity, spare part criticality. The components were ranked according to the maintenance criticality index and thereby implementing the appropriate maintenance strategy.

The Fuzzy VIKOR technique was applied to calculate the ranking of various components of paper industry based on the views and judgment of three maintenance experts. The proposed technique suggested the appropriate maintenance strategy for various components taking into consideration the maintenance criticality index of the components.

The proposed technique will help the maintenance managers to solve a discrete problem with non-commensurable and conflicting criteria. The study will help the industries to reduce the unnecessary maintenance tasks and thereby reduce the maintenance cost. This will help the maintenance practitioners in choosing the best and most effective strategy for the organization with regard to the market and company situation especially in the changing business requirement of Industry 4.0.

The authors develop a methodology to select appropriate sustainable supply chain indicators (SSCIs) to measure Sustainable Development Goals (SDGs) in the global supply chain.

SSCIs are identified by reviewing the extant literature and topic modeling. Further, they are evaluated based on existing SDGs and ranked using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Notably, the evaluation of indicators is a multi-criteria decision-making (MCDM) process within a fuzzy environment. The methodology has been explained using a case study from the automobile industry.

The case study identifies appropriate SSCIs and differentiates them among peer suppliers for gaining a competitive advantage. The results reveal that top-ranked sustainability indicators include the management of natural resources, energy, greenhouse gas (GHG) emissions and social investment.

The study outcome will enable suppliers, specialists and decision makers to understand the criteria that improve supply chain sustainability in the automobile industry. The analysis provides a comprehensive understanding of the competitive package of indicators for gaining strategic advantage. This proactive sustainability indicator selection promotes and enhances sustainability reporting while fulfilling regulatory requirements and increasing collaboration potential with trustworthy downstream partners. This study sets the stage for further research in SSCIs’ competitive strategy in the automobile industry along with its supply chains.

This study is unique as it provides a framework for determining relevant SSCIs, which can be distinguished from peer suppliers, while also matching economic, environmental and social metrics to achieve a competitive advantage.