The manufacturing industry always tries to improve performance amid the trade globalization. Demand and supply uncertainty, and increasingly the intense competition, prosecute the presence of an affective leadership to integrate the company's internal and external resources in improving company performance. This research investigates the role of affective leadership in firm performance through an internally integrated system and external integration in FMCG companies. Data collection used questionnaires, designed with a five-point Liker scale, were distributed to 55 fast-moving consumer goods (FMCG) manufacturing companies. The data analysis used the PLS technique utilizing smart PLS software to assess the validity and reliability of the outer model and to examine the hypotheses developed. The results of the hypothesis testing found that affective leadership can improve internal system integration, external integration, and firm performance. Internal system integration has an impact on external integration but is not strong enough to have a direct effect on firm performance. The internally integrated system has an influence on firm performance through external integration. The company's ability to share information with external partners can improve firm performance through demand fulfillment. The study provides a managerial implication on how to enhance firm performance in the context of internal and external system integration. The finding of this research enriches the current studies in supply chain management.

This research aims to determine the effect of the adoption of teleworking on the development of job exhaustion of the higher education administrative staff in Junín during the crisis of COVID-19. The applied and correlational research was carried out with the participation of 300 administrative workers of higher education by applying a questionnaire of 40 questions. The results obtained show that having teleworking skills reduces emotional fatigue and depersonalization since the collaborator can self-regulate his behavior when faced with stressors. Likewise, these skills generate a positive effect on personal fulfillment, allowing the teleworker to achieve a satisfactory personal fulfillment of having said skills. On the other hand, telework conditions generate a hidden effect on emotional exhaustion, depersonalization and personal fulfillment; therefore, this dimension does not contribute to the reduction or increase of the mentioned dimensions. The work-life balance dimension does not generate any effect on any of the factors. It is concluded that the development of skills for teleworking is a relevant factor to achieve personal fulfillment in teleworkers, while teleworking conditions do not reduce job burnout.

The purpose of this study was to examine the impact of the online social media networks (OSMNs) on productivity at workplace among 88 administrative staff at Prince Sattam bin Abdulaiziz University for the academic year 2020-2021. This study finds that using online social media networks by PSAU’s employees at the workplace enhances their productivity. The majority of the employees (59%) perceive that using the OSMNs at workplace have a positive impact on their productivity. In addition, the majority of the employees (33%) regularly use WhatsApp as a useful online social media network at the workplace. The results also indicate that the majority of the employees (66%) use the OSMNs at workplace more than once a day. Further, the majority of the PSAU’s employees (39%) use the OSMNs at work-place less than half an hour per a day. Furthermore, 39% of the PSAU’s employees use the OSMNs at workplace to keep in touch with their families and friends, and 34% of the employees use the OSMNs to search for work-related information. The results of this study should be useful to policy makers in Saudi Arabia at the country, ministry of education, PSAU, and elsewhere in gaining a deeper understanding on how using the OSMNs at work-place can enhances the employees’ productivity.

Social media serves as a platform or a new area for developing innovation responsive to business advancement. As individuals are the source of knowledge in organizations, individual learning is the focus of organizational learning and development. Ambidexterity is an activity that requires individual learning. The study was carried out in Greater Jakarta, Indonesia. A personal survey questionnaire with convenience sampling was used to collect white-collar workers in Greater Jakarta. Rasch Model Analysis, specifically Person Measure Analysis, was used to filter for bias in the responses because the data was collected through personal references or self-report questionnaires. Structural Equation Modeling (SEM) is used to test hypotheses based on the collected data. According to the statistical results, ambidexterity and social media learning experience significantly impact innovative behavior. It implies that ambidexterity and social media learning experience can improve white-collar workers' innovative behavior. Ambidexterity has a significant impact on the learning experience on social media. It implies that a person with greater ambidexterity will engage in more intense knowledge exploration and exploitation through social media. The study's findings also show that social media experience without ambidexterity has the least impact on innovative behavior. It implies that social media experience without exploratory and exploitative activities does not lead to innovative behavior.

The purpose of this study was to analyze the effect of social media marketing variables on brand image variables and e-commerce customer loyalty variables in Indonesia. The method used in this study uses quantitative methods through online surveys. This study used a sample of 345 respondents who were determined by the snowball sampling method. The research data was distributed using an online questionnaire via Google form. Data analysis of this research uses a SEM model using SmartPLS 3.0 software. Based on data analysis, it can be concluded that the Social media marketing variable has a significant effect on the brand image of e-commerce consumers, the brand image variable has a significant effect on the e-commerce consumer loyalty variable and the Social media marketing variable has a significant effect on the e-commerce consumer loyalty variable.

Despite the increased dissemination of online tools to execute financial transactions, the level of credit card usage adoption among consumers still encounters many challenges. The dissemination and adoption of credit cards to execute online purchases is influenced by certain factors that impact customers' consumption behavior. Exploring and perceiving these factors and challenges is imperative for enhancing the operations of online businesses. This study aims to examine specific factors that affect the adoption of credit cards among customers within the Jordanian online market. The factors this study explores are: Expenditure Level, Welfare of the Individual, Psychological Behavior, Credit Card Knowledge, Regulations and Laws and, finally, Theft and Fraud. This research was conducted through employing the quantitative approach; utilizing a questionnaire on a total of (335) credit card users in Jordan. The research subjects were credit card users (customers) from three Jordanian banks: Arab Banking Corporation, Housing Bank for Trade and Finance, and the Bank of Jordan. The study findings indicated that ‘Individual Welfare’ and ‘Psychological Behavior’ are the strongest influential factors on individuals' adoption of credit cards, followed by ‘Theft and Fraud’, ‘Laws and Legislation’, ‘Credit Card Knowledge’ and ‘Expenditure Level’ respectively in influence. The study recommendation encourages banks to focus more on increasing their clients' awareness regarding credit cards usage in order to enhance their perception of how to behave in case of fraud and theft and increasing their clients' awareness of the financial burdens, pitfalls, and tricks while using a credit card. Moreover, it suggests that banks should increase their marketing efforts for credit cards which can change the behavior and acceptance of individuals towards credit cards adoption.

This paper discusses the application of the Taguchi method to optimize the machining parameters for machining of GFRP composite in drilling for individual responses such as thrust force and delamination factor. Moreover, a multi-response performance characteristic is used for optimization of process parameters with application of grey relational analysis. An orthogonal array (L9), grey relational generation, grey relational coefficient and grey – fuzzy grade obtained from the grey relational analysis applied as performance index to solve the optimization problem of drilling parameters for GFRP composite. Taguchi orthogonal array, the signal-to-noise ratio, and the analysis of variance are used to investigate the optimal levels of cutting parameters. The confirmation tests are conducted to verify the results and it is observed that grey-fuzzy approach is efficient in determining the optimal cutting parameters.

This paper models the process of ordered product design decision making. The problem is formulated by introducing the notion of Quality Loss to quantify the loss of design freedom incurred by the decision makers in the later stages of a cross-functional decision process. In this context, the optimal order is the decision order with the lowest quality loss, whose characterization is one of the contributions of this paper. In this paper, we present a novel decision support system for order in a Make-to-Stock or Make-to-Order production environment. The proposed decision support system is comprised of six steps. The customers are prioritized based on a new method. In this paper, the idea of the algorithm “Knapsack” is used to prioritize customers. Finally, numerical experiments are conducted to show the tractability of the applied mathematical programming model.

This paper addresses a multi items volume flexible system for time dependent decaying items with the concept of machine breakdown and imprecise environment. In this study, partially backlogged shortages have been discussed. All the costs are fuzzified with signed distance method. Numerical examples are given to illustrate the theoretical results and sensitivity analysis is given to validate the results for various parameters.

This paper presents an alternate technique based on fuzzy goal programming (FGP) approach to solve multi-objective programming problem with fuzzy relational equations (FREs) as constraints. The proposed technique is more efficient and requires less computational work than that of algorithm suggested by Jain and Lachhwani (2009) [Jain, & Lachhwani (2009). Multiobjective programming problem with fuzzy relational equations. International Journal of Operations Research, 6(2), 55?63.]. In FGP formulation, objectives are transformed into the fuzzy goals using maximum and minimal solutions elements of FREs feasible solution set. A pseudo code computer algorithm is developed for computation of maximum solution of FREs. Suitable linear membership function is defined for each objective function. Then achievement of the highest membership value of each of the fuzzy goals is formulated by minimizing the sum of negative deviational variables. The aim of this paper is to present a simple and efficient solution procedure to obtain compromise optimal solution of multiobjective optimization problem with FREs as constraints. A comparative analysis is also carried out between two methodologies based on numerical examples.