The Vehicle Routing Problem with Loading Constraints (VRPLC) is strongly related to real life applications in distribution logistics. It addresses the simultaneous loading and routing of vehicles, which are two crucial activities in transportation. Since treating these operations separately may result in impractical solutions, the development of applications for VRPLCs has gained the attention of researchers in recent years. Several heuristic methods have been proposed, but they consider only a limited group of practical characteristics that arise in real world situations. This study proposes a hybrid heuristic method based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic and the Clarke and Wright Savings algorithm, to solve a VRPLC with several loading and routing constraints that have not been considered simultaneously before. Experimental results show that the proposed procedure produces competitive solutions in short processing times. Lastly, the impact of the added operational constraints is also analyzed.

The literature on flow shop scheduling has extensively analyzed two classes of problems: permutation and non-permutation ones (PFS and NPFS). Most of the papers in this field have been just devoted on comparing the solutions obtained in both approaches. Our contribution consists of analyzing the structure of the critical paths determining the makespan of both kinds of schedules for the case of 2 jobs and m machines. We introduce a new characterization of the critical paths of PFS solutions as well as a decomposition procedure, yielding a representation of NPFS solutions as sequences of partial PFS ones. In structural comparisons we find cases in which NPFS solutions are dominated by PFS solutions. Numerical comparisons indicate that a wider dispersion of processing times improves the chances of obtaining optimal non-permutation schedules, in particular when this dispersion affects only a few machines.

This paper is interested in pharmaceuticals distribution which is one of the most important activities and ensures the availability of drug products to a set of customers (pharmacies). The study introduces the Disrupted Vehicle Routing problem with Soft Time Windows since pharmaceutical distributors should respond to increased demands for products to ensure timely and efficient delivery to dynamic demands. We also propose an improved multiobjective local search (IMOLS), which uses methods of neighborhood search such as large neighborhood search (LNS) and variable neighborhood search (VNS) based on a hybrid approach in the optimization of vehicle routes. The algorithm is expected to achieve competitive results compared with previously published studies.

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.

Success key elements are crucial for the improvement and preservation of competitiveness in the ho-tel sector. Hotels thus need efficient employees with best possible quality of work life to remain competitive. This paper investigated the impact of organisational structure (OS) and leadership style (LS) on quality of work life (QWL) among five-star hotels employees in Jordan with job satisfac-tion (JS) as mediator. Questionnaires were distributed among 430 five-star hotel employees to ob-tain the study data. The levels of relationships among the constructs (OS, LS, JS, and QWL) were analysed using partial least squares structural equation modelling (PL-SEM). The results showed a positive relationship of JS and OS with QWL, while JS showed a partial mediating role on the rela-tionship among LS, OS and QWL. Similar studies should be carried out on other sectors in Jordan and in other settings using different perspectives.

The purpose of this research is to develop a conceptual model to explain the relationship between the uniqueness of higher education, student experience and university image. Structural Equation Modeling (SEM) is an analytical technique used to test the model. Data collection is conducted on 268 active students from 49 private universities in Java West. Research findings report the uniqueness of tertiary institutions influences student experience; uniqueness of tertiary institutions influences the image of the University. Moreover, experience of students influences the image of the University.

This study aims to obtain the results of employee performance appraisal through a decision support system (DSS) on situational leadership with work motivation as a connecting variable to employee performance. The use of this type of quantitative research with the number of respondents with a saturated sample technique will make this research more relevant and objective in showing the re-sults. Data analysis using smart PLS 3.0 which resulted in the finding that the decision support sys-tem (DSS) in situational leadership had not been able to contribute to improve employee perfor-mance. It can be concluded that the role of technology in semi structured decision making must be based on sufficient data to help improve employee motivation and performance. In fact, leadership is still used to make unstructured decisions without paying attention to the data stored in the perfor-mance system. Performance indicators are not well-paid attention so that the value generated from this study shows negative results.

With the prevalence of Covid 19, collaborative learning (CL) with the guide of advanced digital learning innovation has become progressively dominant in an assortment of instructional settings making the role of the lecturer more demanding in managing the classroom. In any case, notwith-standing a solid hypothetical and exploration premise, CL has been scrutinized for being excessively applied to all learning circumstances and student types but largely ignored management aspects that lecturers lack guidance and support in dealing with learner behavior. This study investigates the im-pacts of extroversion/ introversion character qualities and collectivism/individualism convictions on students’ collaborative learning preferences. The empirical data consisting of 170 valid datasets were collected from undergraduate students after attending computer-supported collaborative learn-ing of Edmodo and Google Meet. The relationship among construct was assessed with Structural Equation Modeling (SEM). The assessment of information demonstrated that student perceptions of computer-supported collaborative learning have a positive association with students' personality and cultural beliefs. This finding brings the implication that although collaborative learning through a digital platform is compulsory during the pandemic, extroversion/introversion on students' attitudes and students' cultural beliefs should be considered to ensure the effectiveness of instructions.

Solid waste generation in Malaysia is one of the challenging environmental issues which are often neglected by local households. The main purpose of this research is to ascertain the mediating effect of environmental concerns (i.e., egoistic, altruistic, and biospheric concerns) between households’ descriptive norm and injunctive norm to practice the segregation-at-source of solid waste. A total of 400 residents living in townships in nine districts in the state of Selangor were selected via a multi-stage sampling method. A self-administrated bilingual questionnaire was used to collect the research data. As for the mediation test, the present research found that egoistic concern and altruistic con-cern mediated the significant relationship between injunctive norm and intention to practice the seg-regation-at-source of solid waste among the households in Selangor. The present research con-cludes with research implications and provides several avenues for future research in order to create a comprehensive understanding of the segregation-at-source of solid waste policy among Malaysian citizens.