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The purpose of this study is to analyze the effect of human factor training in aircraft maintenance accident mitigation and aircraft safety in post COVID-19 aviation scenarios. The cause of aircraft accidents and details of three decades of selective aircraft maintenance accidents are analyzed to arrive to the significant aviation safety factor. The effect of COVID-19 pandemic and related technological applications to maintain high standards of safety and their applications in aircraft maintenance with respect to the view of human factors are discussed in details.

This paper details the overview of the human errors, error mitigation and need of human factor applications in aircraft maintenance industry for safe air travel. The criticality of aircraft maintenance in keeping aircraft in airworthy condition to provide safe air transportation without delay and to support airline economy is discussed in this study.

The cause of aircraft accidents and details of three decades of selective aircraft maintenance accidents are analyzed to arrive to the significant aviation safety factor. The effect of COVID-19 pandemic and related technological applications to maintain high standards of safety and their applications in aircraft maintenance with respect to the view of human factors are discussed in details. The route of error mitigation and need of high standard technological training with human factor knowledge, to aircraft maintenance students are analyzed in detail with the opportunity of percentages of error reduction.

This study bridges, gained knowledge for aircraft maintenance error mitigation, current accident rates and future training needs for safest air travel through high standard quality maintenance in aircraft and its systems.

Scheduling of aircraft maintenance operations is a gap in the literature. Maintenance times should be determined close to the real-life to schedule aircraft maintenance operations effectively. The learning effect, which has been studied extensively in the machine scheduling literature, has not been investigated on aircraft maintenance times. In the literature, the production times under the learning effect have been examined in numerous studies but for merely manufacturing and assembly lines. A model for determining base and line maintenance times in civil aviation under the learning effect has not been proposed yet. It is pretty challenging to determine aircraft maintenance times due to the various aircraft configurations, extended maintenance periods, different worker shifts and workers with diverse experience and education levels. The purpose of this study is to determine accurate aircraft maintenance times rigorously with a new model which includes the group learning effect with the multi-products and shifts, plateau effect, multi sub-operations and labour firings/rotations.

Aircraft maintenance operations are carried out in shifts. Each maintenance operation consists of many sub-operations that are performed by groups of workers. Thus, various models, e.g. learning curve for maintenance line (MLC), MLC with plateau factor (MPLC), MLC with group factor (MGLC) were developed and used in this study. The performance and efficiency of the models were compared with the current models in the literature, such as the Yelle Learning model (Yelle), single learning curve (SLC) model and SLC with plateau factor model (SLC-P). Estimations of all these models were compared with actual aircraft maintenance times in terms of mean absolute deviation (MAD), mean absolute percentage error (MAPE) and mean square of the error (MSE) values. Seven years (2014–2020) maintenance data of one of the top ten maintenance companies in civil aviation were analysed for the application and comparison of learning curve models.

The best estimations in terms of MAD, MAPE and MSE values are, respectively, gathered by MGLC, SLC-P, MPLC, MLC, SLC and YELLE models. This study revealed that the models (MGLC, SLC-P, MPLC), including the plateau factor, are more efficient in estimating accurate aircraft maintenance times. Furthermore, MGLC always made the closest estimations to the actual aircraft maintenance times. The results show that the MGLC model is more accurate than all of the other models for all sub-operations. The MGLC model is promising for the aviation industry in determining aircraft maintenance times under the learning effect.

In this study, learning curve models, considering groups of workers working in shifts, have been developed and employed for the first time for estimating more realistic maintenance times in aircraft maintenance. To the best of the authors’ knowledge, the effect of group learning on maintenance times in aircraft maintenance operations has not been studied. The novelty of the models are their applicability for groups of workers with different education and experience levels working in the same shift where they can learn in accordance with their proportion of contribution to the work and learning continues throughout shifts. The validity of the proposed models has been proved by comparing actual aircraft maintenance data. In practice, the MGLC model could efficiently be used for aircraft maintenance planning, certifying staff performance evaluations and maintenance trainings. Moreover, aircraft maintenance activities can be scheduled under the learning effect and a more realistic maintenance plan could be gathered in that way.

The manufacturing domain presently focusing on Industry 4.0 (I4.0). One such domain is the automotive sector. The purpose of this study is to analyse the I4.0 research studies with a focus on the automotive sector using a systematic literature review (SLR).

This paper presents a SLR of previous studies on I4.0 characteristics from its inception to performance measures focusing on the automotive sector. A total of 90 papers published in reputed journals during 2014–2020 were collected from major publishers, namely, Elsevier, Springer, Taylor and Francis, Emerald, Institute of Electrical and Electronics, MDPI, etc.

The findings of the study provided vital insights on various perspectives of I4.0 in an automotive organization. Moreover, this systematic analysis would help the automotive industry policymakers in implementing I4.0 in an organization. Based on the SLR, a conceptual framework is established to guide industry practitioners towards I4.0 implementation. The review findings could be used to carry out future studies in assessing the readiness of I4.0 in the organization with the help of a survey.

The limitation of the study is in the adoption of the sampling approach. In the present study, conference papers and refereed journals have been considered based on the relevance of I4.0 in the automotive industry. As I4.0 is a growing concept, non-refereed articles, book chapters and white papers may cover practical aspects regarding I4.0 implementation that need to be considered for depth analysis. Moreover, the framework needs to be validated with various automotive industries for ensuring practical validity.

The unique contribution of the study is the SLR of I4.0 in manufacturing with a focus on the automotive sector.

This paper aims to assess the farming community’s perception on important parameters of climate change and identify major practices and technologies adopted to mitigate the impacts of climate change and their determinants in mountain district of Nepal. Being an agrarian economy and dependent on monsoon rain, the impact of climate change on agricultural productivity and production has been experienced. Different adaptation strategies have been adopted by the communities to cope with the consequences of climate change.

Four village development committees (VDCs) situated in the buffer zone of Langtang National Park of Rasuwa district representing rice, wheat, maize and potato production area was purposively selected for this study. A two-stage sampling technique was adopted for data and information collection. Thirty households from each VDC were randomly selected. Data on the socio-economic and climate change perception were collected using structured questionnaire. A binary logistic regression technique was used to identify the determinants of climate change adaptation technologies and practices.

The farmers’ decisions whether to adopt climate change adaptation technologies are governed by the size of landholding, perceived threat of climate change to food security, education level and gender of the interviewee, perception on the increased incidence of droughts during rainy season and income received from the off-farm sources. In a community where agricultural activity is the dominant means of living, adaptive strategies help to increase the capacity of a farming system to survive external shocks and cope with the consequences.

The assessment of farm-level adaptation strategies and factors influencing their adoption decision is important to formulate policies and design programs. This will also help to recognize adaptation as a tool for managing a variety of risks associated with climate change in agricultural sector.

In 2020, the logistics market in Malaysia was valued at USD 37.60 billion, and it is projected to grow to more than USD 55.0 billion by 2026 at a compound annual growth rate (CAGR) of more than 4%. However, more information is needed about the impact of green logistic practice determinants by the local SMEs on the market share. This study serves as a focal point by examining the factors involved by offering a conceptual framework of determinants and their potential outcomes. This study contributes by demonstrating a conceptual, theoretical framework derived from the synthesis of two theory such as the Resource-Based View theory and the Diffusion of Innovation Theory. At the same time, it offers a holistic approach with an in-depth understanding of the Technological and Organizational factors of SMEs. The relationship between the implementation of green practices and organizational performance is also explored.

The purpose of this study was to assess the effect of vacuum tumbling and red beetroot juice (RBJ) incorporation on quality characteristics of marinated chicken breast and leg meat cuts.

Vacuum tumbling of breast and leg meat cuts was carried for a duration of 2 h and compared with control (0 h tumbling) and traditionally marinated (6 h) meat cuts. Vacuum-tumbled treatments were also marinated using RBJ in place of water to assess the combined effect of RBJ and vacuum tumbling. All the cuts were cooked in an oven at 170°C for 40 min. Quality characteristics of fresh and refrigerated products were analysed.

Vacuum tumbling for 2 h resulted in a significant (p < 0.05) increase in marinade pickup, water-holding capacity (WHC), cooking yield, moisture and ash content and a significant (p < 0.05) decrease in hardness, gumminess, chewiness and shear press values in both types of meat. Breast meat treatments had significantly (p < 0.05) higher WHC, moisture, protein, cohesiveness and gumminess and significantly lower fat content, hardness and shear press values than leg meat treatments. Control breast and leg meats had marinade pickup of 9.19 and 9.31 per cent and cooking yield of 69.08 and 68.31 per cent, respectively, whereas corresponding values for treated breast and leg meats varied from 11.28 to 11.98 per cent and 73.32 to 74.94 per cent, respectively. Sensory scores declined significantly (p < 0.05) during refrigerated storage. On the 12th day of storage, control breast and leg meat cuts had acceptability scores of around 5.0, whereas all other treatments had acceptability scores between 6.0 and 7.0 on an eight-point scale, with RBJ-treated products having the highest acceptability. All the products were also microbiologically safe up to the 12th day of refrigerated storage.

The research is valuable to meat processors because vacuum tumbling for 2 h using RBJ as marinade can be used in place of 6 h of traditional marination for developing marinated chicken breast and leg meat products.

The case explores information technology (IT) company Mindtree’s journey of 20 years from the time it was founded in 1999 to be different from others, and how it became a target for acquisition by an Indian diversified conglomerate in 2019. It offers insights into developing organizational culture and values in an organization, threats faced by a company when promoters dilute their shareholding, and the strategies followed by the acquirer and the target firm. It also deals with the challenges in the acquisition of a knowledge service digital firm. After working through the case and assignment questions, students will be able to: identify the circumstances under which a company can become a target for hostile takeover; describe motivations of the acquirer firm in an acquisition; distinguish between acquisition and hostile takeover, and discuss salient features of Securities and Exchange Board of India (substantial acquisition of shares and takeover) regulations, 2011; list the defenses a target firm can adopt to ward off hostile acquirer; explore strategies followed by acquirer and target firms; analyze important ingredients of organization culture, and importance of cultural congruence in an acquisition; and discuss challenges faced by an acquirer in India, namely, legal, retention of clients and key people in the target firm particularly in hostile environment.

The case explores how ten IT professionals founded mid-tier IT services company Mindtree in 1999 in Bengaluru, India (home to Infosys and Wipro) to be different from others – by inserting themselves at a higher level in the value chain, being philanthropic as a part of broader business strategy to attract a certain kind of employee and customer. It developed a culture of equality, consideration and respect. Its attrition rate of 12 to 13 per cent was significantly lower than the Industries. Mindtree crossed annual revenue of US$1bn for FY 2019 and was growing at twice the industry’s growth rate. The most attractive part was that its proportion of revenue from digital services was about 50 per cent as compared to 25-35 per cent of other services vendors. With time, the share of promoters/founders declined and increased one investor’s shareholding of V. G. Siddhartha and his related entities. In early March 2019, the promoters’ stake was 13.32 per cent while Siddhartha had 20.32 per cent. Larsen and Toubro (L&T) one of India’s conglomerate entered into a share purchase agreement on March 18, 2019 with Siddhartha to acquire his 20.32 per cent stake. Immediately, L&T asked its broker to purchase up to 15 per cent of share capital of Mindtree at a price not exceeding INR 980 per share (each share of face value INR 10). This would trigger an open offer by L&T to purchase additional 31 per cent shares of Mindtree. The action of hostile takeover bid by L&T evoked emotional criticism from Mindtree founders. Mindtree efforts to defend itself could not materialize. L&T’s stake crossed 26 per cent on May 16, 2019. After Indian regulator SEBI’s approval, L&T’s open offer to buy shares from Mindtree shareholders commenced on June 17, 2019. The case examines motivation of the acquirer firm particularly when it is a conglomerate, and how a well-performing company became a target for hostile takeover. It looks at vulnerabilities of a target firm, and defensive steps a firm can take to fence itself against such takeover. The case also explores how organizational culture is built in a people-oriented business, namely, digital services, and what role it plays in a merger of two firms.

The case is suited for postgraduate students of management, as well as those undergoing executive courses in management.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

The COVID pandemic has prompted B2B and industrial marketing scholars to understand more about how external disruptions impact parties involved in B2B transactions. This paper aims to adopt an ecosystem perspective to conceptually classify the interactions between actors involved in B2B ecosystems.

This conceptual paper presents a framework across multiple levels of ecosystem interactions (at micro, meso and macrolevels) to illustrate how value cocreation and knowledge flows (as mechanisms underlying B2B relationships) are related to firm performance.

Based on this framework, this paper offers propositions and several research questions about the effects of disruptions and how they propagate among these essential business ecosystem elements.

This conceptual framework underscores the vital role of relationships and interactions in shaping B2B ecosystems, especially during disruptive periods. With a greater understanding of how these interactions operate across levels (micro, meso and macro), scholars and practitioners may be better able to navigate disruptive periods.