This paper addresses the sustainable closed-loop supply chain (SCLSC) design problem regarding selecting a supplier under total quantity discount with demand uncertainty and logistic flow uncertainty. The proposed model considers the three pillars of sustainability: the economic, environmental, and social realms. The model deals with the costs incurred by products-related manufacturing and minimizes the carbon dioxide emissions resulting from different manufacturing processes, as well as the attendant rate of injuries among the workers. Python edition 2019-07 software with the SCIPY solver was used to solve the model, using a sequential least squares programming algorithm (SLSQP) to obtain optimal solutions. A numerical study was conducted to validate the model. A sensitivity analysis was conducted to address the effects of both types of uncertainty on the optimal solution. It was found that the effect of a high rate of demand uncertainty is more severe than the effect of the uncertainty of the flow logistics in the reverse direction since the former generated a lower value of the optimal solution than the worst-case scenario generated by the uncertainty budget. Moreover, the higher the weight of environmental and social objectives, the higher the proportion of recycled products from the total production. This study proposes a robust optimization model for an SCLSC that considers two types of uncertainty: the uncertainty budget that is used for the logistics flow in the reverse direction for refurbished and redesigned products and the box of uncertainty that is used to address the demand uncertainty.

Global competition and economic globalization are forcing countries' governments to devise encouragement support programs and formulate exporting policies to help SMEs export, compete, and survive in foreign markets. This study examines the mediating role of national export support and encouragement programs (NESEPs) in clarifying the impact of determinants of market environment information on the SMEs' export financial performance (EXFP) and SMEs' export strategic performance (EXSP) based on a resource-based view, which helps understand novel holistic relationships between them. Data from 106 exporting SME firms working in the Kingdom of Saudi Arabia were collected using an online questionnaire survey. Regression path analysis from structural equation modeling was used to test the study's model relationships. The most important positive findings that emerged from this study are: Determinants of market information acquisition (DMIA) will positively influence SMEs' EXFP and NESEP. Determinants of market information dissemination (DMID) will positively influence SMEs' EXSP. Determinants of market information responsiveness (DMIR) will positively influence NESEP. NESEP will positively mediate the effect of DMIA and DMIR on SMEs' EXSP. The study’s theoretical and social implications and limitations are discussed in the concluding sections. Furthermore, directions for future research are provided.

Most of the organizations today look forward to streamlining their business with the rapid needs of the society. However, they do not consider the holistic view of various digital driving factors. The paper aimed to develop a structural framework using the enablers of Digital Transformation (DT) by applying qualitative and rational approaches to develop a conceptual model of DT adoption for various industries. The assimilated approach of Delphi and Interpretive Structural Modelling demonstrated the qualitative data-driven theoretical structure by identifying fourteen enablers of DT and developed a logical model in nine levels. The driving and dependency powers of each enabler were portrayed in MIC MAC analysis. The government regulation and market pressure found as key drivers with strong driving and low dependency powers occupying the lowest level which influences customer demand, behavior and expectations and process, performance improvement of the business. The model demonstrates a deep understanding of global firms to leverage various dimensions while taking transformation decisions in their business process and gain a competitive edge. Further, any organization that looks for adopting digital transformation can consider these factors or models in deciding the implementation process. It recommends researchers to validate the model or may prioritize the factors and sub-factors for multi-criterion based decision making process for unique findings.

Cement & material sector is instrumental in infrastructural development of any economy. The same holds about Saudi cement sector which has contributed substantially to the economic and construc-tion boom in Kingdom of Saudi Arabia (KSA). The cement sector of KSA holds the highest place among other GCC countries. Though, during the last couple of years, the sector seems to be grap-pled with capacity and weighted down due to certain reasons. Nevertheless, almost all of the cement companies in KSA are underplaying their actual capacities. Still, plenty of untapped growth oppor-tunities for cement sector are available in KSA and other GCC countries. Henceforth, considering the growth potential and taking cue from the current scenario of KSA cement sector, the current study endeavors to measure the efficiency of listed cement companies in KSA. The study endeavors to be engrossed in identifying a set of companies which plays on efficiency frontier. Therefore, the technical efficiency performance of fourteen listed cement companies in KSA was measured using Data Envelopment Analysis (DEA) methodology. Two basic models of DEA methodology (i.e. CRS & VRS) were used to estimate the pure and technical efficiency of identified DMUs over a pe-riod of four years from 2016 to 2019. The study reveals that over a period of four years and on an average efficiency scale, only 23% of the firms were purely technically efficient on a CRS scale, while 46% of the firms were technically efficient. Only 23% of the firms were scale and technically efficient. Though, companies in the sector have a vast potential to outperform on efficiency front. Yet, the overall efficiency level among Saudi cement companies are remained depressing. Moreo-ver, the study has noticed that the companies which are inefficient did not have a considerable dis-tance from the efficiency frontier. The study also provided significant insights on the input factors causing inefficiency and suggestion to achieve the total technical efficiency. Furthermore, the effi-ciency analysis also provided benchmarking firms, which are efficient under several criteria for oth-ers to imitate their best practices for becoming a significant player on efficiency frontier.

Most global studies have, to a greater extent, underscored the importance of Total Quality Management (TQM) practices and some marketing aspects concerning the organizational performance. Most studies have focused on establishing the level to which TQM practices influence customer satisfaction and not the whole organization. There is also little evidence on how marketing practices influence organizational performance. This study therefore seeks to assess the impact of TQM practices and marketing on organizational performance. Data was collected from a sample size of 289 respondents who were employees of the different manufacturing industries in Saudi Arabia. Data was analyzed using SPSS and Pearson’s rank correlation coefficient was used to establish the relationship between study variables. The study findings confirmed the presence of a relationship between TQM practices and organizational performance. Similarly, there was a positive relationship between marketing practices and organizational performance. The study concluded that the TQM practices and marketing are great influencers of quality hence should always be applied in organizations.

The present study aimed at identifying the reasons for the customer's exit and determining their effects on social word-of-mouth through the means of social media applications. Four customer exit drivers were selected after a review of the literature: service failure, service recovery failure, price problems, and customer dissatisfaction as independent variables. The social word-of-mouth was also chosen as a dependent variable. The study sample consisted of 468 users of the social media. The criterion of entry into the sample was the experience of at least one restaurant and the publication of a comment via social media. The number of electronic questionnaires filled by users were 355 questionnaires. The questionnaire consisted of 20 items measuring the study variables, which were extracted after reference to the previous study related to the subject of the study. After confirming the suitability of the study model, the hypotheses were tested. The results show acceptance of all hypotheses, which means that the four customer's exit drivers lead to negative messages through social media, i.e., negative social word-of-mouth. The study recommended that firms should take care of the drivers of customer exit first and then participate in the means of social media to justify their position and contribute to the formulation of a positive opinion. The contribution of this study to literature is that it distinguishes between two types of customer exit drivers that have been studied, which are called controllable drivers by the firm, compared to another type of exit drivers.

The present study's primary goal is to examine selected financial risks and financial performance of commercial banks listed on the Bahrain Bourse from 2014 to 2021. However, as independent factors, chosen financial hazards include capital risk, liquidity, and bank size as a control variable, while financial performance as a dependent variable is assessed by return on equity. The panel regression analysis of data technique was used to attain the study goal. Whereas the statistics for the banks were gathered from their annual financial reports. A fascinating conclusion was the discovery of strong correlations between capital risks, bank size, and financial performance. The findings also revealed a negligible link between liquidity concerns and financial success. Due to the limitations of the present study, several ideas for future research may be suggested, such as performing research on other financial hazards, other financial institutions, and other financial performance metrics that are not included in the current research.

Saudi Arabia is attempting to structurally transform itself to move away from its dependence on oil. Towards this, its education sector plays an important role. It provides the economy with the needed graduates. It is highly desirable that the education sector of the country attains and maintains quality standards. This study identifies the three dimensions of teaching staff, administrative staff and systems towards the Total Quality Management in a University setting. The study finds a significant difference between the sample respondents over the satisfaction with the faculty, staff, and systems. Further, the study uses the method of logistic regression to analyze the responses of University students’ perspectives of quality. The results indicate that the odds of being satisfied with the University are the highest if the students are satisfied with the systems. It followed by faculty and then the non-teaching staff. Improving the quality of faculty, staff, and systems in education services is needed to achieve the structural transformation desired by the country.

This paper aimed to examine the determinants affecting students’ Grade Point Average (GPA) at the colleges of science in Prince Sattam Bin Abdul-Aziz University (PSAU). The study applied two approaches of Ordinary Least Square Method (OLS) and Quantile Regression (QR) to investigate the relationship between GPA and different factors; including secondary school rate, achievement test, gender, and department. The data were collected from the Deanship of Admissions and Registration for the academic year (2018) at PSAU. The sample size included (175) students selected from four departments. The data were analyzed using SAS and SPSS programs. The important results are: secondary school rate, achievement test, and gender were revealed to be variables that significantly impact GPA at all quantile levels. At 0.95 quantile the variable department has a significant effect on GPA. The OLS method revealed the significant effect of all four variables secondary school rate, achievement test, department, and gender on GPA. The study recommended that policy makers in higher education should think to add a new criterion for admission according to the privacy of every college or university.

The study focused on examining the social customer relationship management impacts on the customer loyalty of five-star hotels in Saudi Arabia. Customer relationship management included the dimensions of customer value, long-term partnership with the customer, customer knowledge, reliance on technology, trust, and social media communication. The study population consists of the customers of five-star hotels in Saudi Arabia. A convenience sample was taken from 500 customers, while the validly retrieved responses were 413. A quantitative approach was conducted in statistical analysis through SPSS and AMOS software. The study demonstrated that social customer relationship management dimensions are impacting the customer loyalty of five-star hotels in Saudi Arabia. Subsequently, the recommendations centered on the establishment of a complaints handling unit to speed up service, identify problems, identify the sites of deficiencies, and take the necessary and appropriate solutions to these problems.