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This paper is to explore how cross-functional integration (CFI) of production-marketing can impact the firm's build-to-order (BTO) competitiveness, marketing performance (MP) and financial performance (FP).

Empirical study with the structural equation modeling approach is applied. Six hypotheses are constructed and tested based on survey data collected from Chinese manufacturing firms.

The survey data supports that production-marketing integration (PMI) improves BTO competitiveness (BTOC) and MP and that BTOC also positively affects marketing outcome which, in turn, impacts a firm's FP. The results reveal that CFI of production-marketing is an effective approach for achieving the BTO manufacturing strategy and can improve organizational performance.

The paper uncovers the role of CFI of production-marketing in BTO manufacturing strategy and its impacts on a firm's MP and FP and provides important managerial implications for practitioners to improve organizational time-based competitiveness and performance in today's time-based competition era.

This paper employs the gravity model to investigate how the growth of China’s textile and clothing (T&C) exports is displacing the exports of other Asian developing countries over the 1990-2015 period. Aggregate analyses were undertaken, and the endogeneity of Chinese exports were accounted by applying instrumental variables with country fixed effects. It was found that there was a negative impact of China’s emergence on T&C exports on other Asian developing countries. We further explored whether such displacement effect varies across Asian countries and the results showed that a more pronounced effect was found in low-income countries than high-income ones. Our findings suggest that the export competitiveness of China’s neighbors, i.e. both more and less developed Asian countries, are affected by the emergence of China in T&C Trade. The implications of China’s One Belt, One Road initiative are also discussed.

The purpose of this paper is to determine the role of service quality (SQ), trust and commitment to customer loyalty (CL) for telecom service users. Further, the moderating role of gender, marital status and connection type within the model was tested.

A measurement model was created based on valid 615 responses from Indian TSUs for SQ, trust, commitment and loyalty with the help of partial least squares structural equation modeling (PLS-SEM). Multi-group analysis (MGA) was conducted to understand the moderating effect of marital status, gender and connection type within the model.

The results suggest that, out of five dimensions of SQ, only responsiveness, assurance and empathy have a significant positive relationship with both commitment and trust. Tangibility has a significant positive relationship with trust only. Both commitment and trust have a significant impact on loyalty. It was noticed that both commitment and trust act as mediators between three SQ dimensions (assurance, empathy and responsiveness) and CL. MGA revealed that empathy and responsiveness positively induce trust in telecom users who are single. Whereas, assurance increases commitment toward telecom service providers in married users. Assurance and empathy significantly contribute toward commitment and trust, respectively, in male users as compared to females. Empathy was found important for postpaid users for trust-building, whereas trust was found to be more important for prepaid users to stay loyal to the service provider.

This article contributes toward understanding the role of SQ, trust and commitment to CL moderated by marital status, gender and connection type in an integrated model concerning telecom service.

The main purpose of this study is to investigate the effect of learning culture and knowledge sharing (KS) on organizational effectiveness (OE). This study also proposed to investigate the role of employee competency in organizational success.

This study is based on the primary and secondary sources of data. The primary data comprises 392 responses from different information technology firms located in India, whereas secondary sources are based on journals, reports, company manuals, etc. The data was analyzed in partial least square-structural equation modeling using SMART-PLS 3.3 software.

This study confirms the conceptual model with the collected data. The key contributors to the model are organizational learning culture (OLC), KS, employee competencies (EC) and OE. The OLC and KS are the independent variables, and OE is the dependent variable, whereas the EC is the mediating variable in the research model. The findings reveal that there is a significant OLC on KS, EC and OE. Likewise, the relationship between KS and OE is also significant. The mediation analysis confirms the EC is significant for the relationships. However, the mediating effects of KS on the relationship between OLC and EC are not significant in this research.

An effective learning culture that leads to an increase in KS activities eventually enhances EC and promotes OE. It indicates that strengthening the learning culture will result in the promotion of knowledge sharing, and it is obvious that the employees’ competencies will increase when the employee is skilled and knowledgeable.

With references to different theories, this study provides an integrated model that shows the relationships between OLC, KS, EC and OE. By strengthening the OLC and KS, this relationship is benevolent to the success of the organization. The created framework paves the way for scholars to further explore insights from inside each component.

The purpose of this paper is to explore the increased research attention gained by sustainability in food supply chain management. Although previous review studies have focused on aspects such as traceability, food safety, and performance measurement, sustainability has rarely been considered as a means of integrating these issues.

The paper presents a comprehensive review of the literature on food sustainable supply chain management (FSSCM). Using systematic review methods, relevant studies published from 1997 to early 2021 are explored to reveal the research landscape and the gaps and trends.

The paper shows the building blocks and the main research directions in FSSCM, particularly considering the opportunities in “neglected” emerging countries. Insights are provided into the various elements of the sustainability supply chain in the food industry, which have previously been analysed separately.

Only a few researchers have systematically reviewed the literature or taken a bibliometric approach in their analyses to provide an overview of the current trends and links between sustainability and food supply chain management.

The purpose of this paper is to identify the factors affecting learners' perception of e-learning during the Coronavirus-2019 (Covid-19) pandemic. Furthermore, it investigates mechanisms that enhance students' engagement in e-learning, especially under the constraints created by the pandemic.

Quantitative research approach was used, and data were collected using a structured questionnaire. The sample consisted of 163 undergraduates registered at the Faculty of Management Studies of the Open University of Sri Lanka (OUSL). The structured questionnaire was designed taking into consideration learners attached to different regional centers and study centers of the OUSL.

As per the findings, performance expectancy, social influence, effort expectancy and service quality are the factors which have significant effects on students' “intention to use” e-learning as a method of pursuing education. Furthermore, it was observed that 65.6% of the students had access to technology through mobile phones, while 53.4% of the students had engaged in e-learning for the first time. This was mainly due to restrictions that were imposed during the Covid-19 pandemic.

The study will help in formulating policies and introducing procedures in relation to online teaching-learning models to be used by both teachers and learners, especially in similar pandemic situations in the future.

This study will assist to determine the effectiveness of the e-learning system used by the OUSL. The findings highlighted the importance of improving information technology (IT) facilities available at all the regional and study centers across Sri Lanka.

Conservation agriculture-based wheat production system (CAW) can serve as an ex ante measure to minimize loss due to climate risks, especially the extreme rainfall during the wheat production season in India. This study aims to examine whether farmers learn from their past experiences of exposure to climate extremes and use the knowledge to better adapt to future climate extremes.

The authors used data collected from 184 farmers from Haryana over three consecutive wheat seasons from 2013-2014 to 2015-2016 and multivariate logit model to analyse the driver of the adoption of CAW as an ex ante climate risk mitigating strategies based on their learning and censored Tobit model to analyse the intensity of adoption of CAW as an ex ante climate risk mitigation strategy. Farmer’s knowledge and key barriers to the adoption of CAW were determined through focus group discussions.

The analysis shows that the majority of farmers who had applied CAW in the year 2014-2015 (a year with untimely excess rainfall during the wheat season) have continued to practice CAW and have increased the proportion of land area allocated to it. Many farmers shifted from CTW to CAW in 2015-2016.

While farmers now consider CAW as an ex ante measure to climate risks, a technology knowledge gap exists, which limits its adoption. Therefore, designing appropriate methods to communicate scientific evidence is crucial.

This paper uses three years panel data from 184 farm households in Haryana, India, together with focus groups discussions with farmers and interviews with key informants to assess if farmers learn adaptation to climate change from past climate extremes.

This study aims to present a novel methodology for the evaluation of tribological properties of new nanocomposites with the A356 alloy matrix reinforced with aluminium oxide (Al₂O₃) nanoparticles.

Metal matrix nanocomposites (MMnCs) with varying amounts and sizes of Al₂O₃ particles were produced using a compocasting process. The influence of four factors, with different levels, on the wear rate, was analysed with the help of the design of experiments (DoE). A regression model was developed by using the response surface methodology (RSM) to establish a relationship between the observed factors and the wear rate. An artificial neural network was also applied to predict the value of wear rate. Adequacy of models was compared with experimental values. The extreme values of wear rate were determined with a genetic algorithm and particle swarm optimization using the RSM model.

The combination of optimization methods determined the values of the factors which provide the highest wear resistance, namely, reinforcement content of 0.44 wt.% Al₂O₃, sliding speed of 1 m/s, normal load of 100 N and particle size of 100 nm. Used methods proved as effective tools for modelling and predicting of the behaviour of aluminium matrix nanocomposites.

The specific combinations of the optimization methods has not been applied up to now in the investigation of MMnCs. In addition, using of small content of ceramic nanoparticles as reinforcement has been poorly investigated. It can be stated that the presented approach for testing and prediction of the wear rate of nanocomposites is a very good base for their future research.