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This study aims to examine the effect of motivating language on employee performance and assesses the mediating roles of organisational citizenship behaviour and employee engagement between motivating language and employee performance in the Indian health-care sector, which is a highly demanding work environment, wherein employee burnout is high.

The study was in the context of COVID-19 pandemic set for health-care workers in India. To collect data and test the proposed research model, 328 questionnaires were respondent by multi-level health-care professionals from private and government hospitals in North India.

The findings suggest that leader’s motivating language is crucial for health-care leaders, inducing employee’s performance in context to patientcare, safety and satisfaction. Underpinning theory of leader member exchange substantiates that the role of leader is pivotal in daily interaction with the stakeholders. Self-determination theory of motivation is determined by psychological needs satisfaction inducing employee engagement and organisational citizenship behaviour, amplified through the leader’s motivating language, resulting into improved patientcare and patient safety. The findings state that leader’s motivating language impacts the high culture context like health-care professionals, as observed in the Indian health-care sector during COVID-19. The findings are indicative of developing non-cognitive personality traits for managerial skills.

The study substantiates the pivotal role of the leader’s communication with stakeholders such as patients/attendants and health-care staff. The findings, which are an indicator of patientcare, as an outcome of patient compliance, will be indicative of developing the non-cognitive skills in the personality traits of managerial skills, inducing patients’ trust in their health-care providers, using motivating language. Therefore, the health-care professionals must be trained in the application of motivating language with stakeholders, namely, patients/attendants and staff.

The findings state that leader’s motivating language impacts on employees of high culture context like health-care professionals, as observed in the Indian health-care sector during the recent global medical emergency of COVID-19, whereas the earlier studies posited leader’s motivating language to be effective on employees with low-cultural context. The role of leader is pivotal in daily interaction with the stakeholders, namely, patients/attendants and health-care staff.

The purpose of this paper is to develop a sensitive and cost effective colorimetric sensor for detection of methyl parathion (MP) using simple circuitry. A simple and sensitive concept of colorimetric sensor instrument represents a rapidly expanding field of sensor techniques to monitor MP neurotoxins is described within certain conditions of producing color in samples. The variation of intensity of color with concentration provides discrimination between different concentrations of MP. The colorimetric instrument displays well‐defined signals towards hydrolyzed samples of MP.

The principle of light intensity measurement has been applied to measure various concentrations of MP based on Lambert‐Beer theory. This device and its processes are useful for quantitative analysis of MP. The detection limits were found within a range of 0.1‐1.5 ppm.

The experiments from sophisticated analytical techniques are costly and time‐consuming processes that validate the proposed system.

This paper's original proposition of using quantification of MP with colorimetric sensor instrument obtained promising results.

The colorimetric sensor instrument provides a new method for quantification of MP in unknown samples within detection limits.

The purpose of the study is to identify the factors affecting the entrepreneur's choice of the dairy value chain and evaluate the impact of the value chain on farm performance (profit).

Primary data were collected from dairy entrepreneurs in India, covering nine states. A multinomial treatment effect model (controlling for selection bias and endogeneity) was used to evaluate the impact of the choice of the value chain on entrepreneurs' profit.

Dairy entrepreneurs operating in any recognized value chain other than the value chain driven by the consumer household realize a comparatively lesser profit. Dairy farmers have established direct linkages with customers in urban areas – who could pay premium prices for safe and quality milk. Food safety compliance is positively associated with profit and entrepreneurs (who have undergone formal training in dairying) preferred partnerships with a formal value chain. The prospects of starting a dairy enterprise are slightly higher in villages compared to urban areas.

Dairy entrepreneurs can make a shift in accordance with the study's findings and boost their profitability. It aids in comprehending how trainees (who obtained advice and training for raising dairy animals from R&D organizations) and non-trainee dairy farmers make value chain selections, which ultimately affect profitability. However, purposive sampling and a small sample size limit the universal implications of the study.

Developing entrepreneurial behavior and startup culture is at the center of policymaking in India. The findings imply that the emerging value chain not only enhances the profit of dairy farmers by resolving consumer concerns about food safety and the quality of milk and milk products but also builds consumer trust.

This paper offers insight into how the benefits of dairy entrepreneurs vary with their participation in the different value chains. The impact of skill development/training programs on value chain selection and farm profitability has not yet been fully understood. Here is an attempt to fill this gap. This paper through light on how trained and educated dairy entrepreneurs are able to establish a territorial market by approaching premium customers – this is an addition to the existing literature.

This study describes a series of experiments investigating the upper hot layer temperature profile in a confined space under different ventilation conditions for porosity-controlled wood crib fires for pre-flashover conditions.

Full-scale compartment (4 m × 4 m × 4 m) experiments were carried out for four-door openings, i.e. 100%, 75%, 50% and 25% of the total vent area (2 m × 1 m) with the wood crib as a fuel load. The temperature of the upper hot smoke layers of the compartment was recorded with the help of four layers of thermocouples for varying vent areas.

The effect of ventilation on the properties, i.e. mass loss rate, enclosure temperature, heat release rate and carbon monoxide (CO) gas concentration, has been measured and analyzed. The effect of ventilation on heat flux and flame temperature has also been studied. Compartment gas temperature has been examined by five wood crib burning stages: Ignition, growth, steady burning, recess and collapse.

Findings demonstrate that the influence of vent openings varies for the burning parameters and upper layer temperature of the compartment. The current results are beneficial in analyzing thermal risks concerning compartment fire and fire safety engineering projects.

This study aims to set out to develop and validate a new instrument to measure the multi-dimensional nature of co-opetition in corporate responsibility and sustainability (CRS). It is anticipated that this instrument will prove useful to firms wanting to adopt measures that support relevant sustainability strategies.

The scale development concerns three separate components, namely, item generation through expert interviews; a pilot study conducted for scale purification; and a final study for scale confirmation and validation, respectively. The final study comprises 215 firms across 11 sectors in Australia that engage in co-opetitive alliances for CRS activities.

This study empirically validates the distinctiveness of three dimensions (commonality-driven, competition-driven and collaboration-driven) of co-opetition in relation to CRS resulting in a 15-item multi-dimensional scale. The three dimensions were found to be important aspects both in terms of scale validity and organisational consideration.

This study proposes a new research area regarding the proposed framework, as well as practical strategies for practitioners when considering co-opetition and their firm’s engagement in CRS activities.

Prior studies in similar areas have mainly comprised conceptual or qualitative approaches and do not tend to focus on all three aspects of co-opetition, corporate social responsibility and sustainability.

The case concerns strategy.

This study is applicable to information system, development sector and application of technology in development sector.

Krutika Terracotta Unit is a small unit located in Bhubaneswar, Odisha (India), owned by Mr Tarun Tapan Sahoo. The organization product portfolio varies from decorative statues, pots and vessel to customized products demanded by customers. Organization is also involved in training and renting the products for traditional fairs, marriages and religious ceremony in Bhubaneswar along with order sales. The case attempts to get a close picture of the industry. The exercise of developing the vision, mission, and goals for the organization was carried out and an attempt was made to align the information system with the business objectives even though the organization does not have a very structured organogram. Using BIS will surely reduce manual work and will give qualitative output. There will be lesser hassles in management. The defined and integrated approach will also help in taking strategic decisions well. The objective is to develop and apply well-structured BIS which can be integrated with the existing system so as to develop the terracotta organization in terms of reachability and profit-making with better decision-making capacity.

To learn about the business model of a handicraft marketing organization; to learn about the processes involved in traditional art form of Terracotta; to go through the exercise of creating vision, mission, goals of the organization through mutual discussion and expectation of owner; to determine how BIS helps in achieving higher productivity in Krutika Terracotta Unit; and to get an idea about how NPV calculation and social ROI should be measured for finding feasibility of technology investment.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Defence statement has been uploaded. Consent form to publish has been uploaded.

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

Strategy, strategic management, market and product analysis.

The case is intended for a business strategy course in management. The target participants are MBA students specializing in strategy area as well as middle level and senior level managers from the industry, who come for an executive programme in management science.

Year 2009, Mr Pawan Kumar (General Manager, Halonix Limited) was facing a decision-making situation in the organization. Being one of the most experienced and oldest employees of Halonix (incorporated as Phoenix Lamps Ltd in 1991), he had witnessed the tremendous growth of the company since its inception in 1991. The company was having a global brand image in automotive halogen lamps and became a dominant player in compact fluorescent lamp (CFL) market in India by 2007. With the increasing competition and change in market dynamics, the company needed to decide upon the future product portfolio mix and strategy to be adopted to gain the maximum benefit and win over the competition in both the product segments. The automotive halogen product segment was generating higher margins but having relatively slow growth. The CFL product segment was a growing market but was generating low margins due to increasing competition from entry of large number of players.

The theoretical concepts, which will be explored in this case, involve the following: the importance of industry structure analysis in understanding the basis of competition. The importance of value-chain analysis in strategic planning. The importance of Boston Consulting Group growth-share matrix in evaluating the product portfolio mix having different growth drivers and target segments?

Teaching notes.

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability.

In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance.

In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently.

There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone.

The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.

In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (T_on) and pulse off time (T_off) – on various response characteristics such as material removal rate (MRR), surface roughness (R_a) and electrode wear rate (EWR).

A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization.

For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, T_on = 200 µs and T_off = 45 µs), R_a (I = 14 A, T_on = 100 µs and T_off = 25 µs) and EWR (I = 17 A, T_on = 150 µs and T_off = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs T_on and 25 µs T_off) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting.

To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.