Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.

Studying the factors in influencing the users’ intentions to adopt Big Data technology in Malaysia is crucial. This study adopted three grand theories which consisted of Dissemination of Innovation (DOI) theory, Technology Acceptance Model (TAM), and Technology-Organization Environment (TOE) framework. The model specifies technological, organizational, and environmental factors as determinants of the users’ intentions to adopt big data technology. This study aims to review the technology, organizational and environmental factors that can determine the intentions towards big data technology adoption. A total of 224 questionnaires were obtained and screened. Data was analyzed using the Partial Least Square Modelling of Structural Equations due to one of the best software for verifying structured data on structural equations modelling (SEM) Smart PLS 3.0 as analytical tools. This study finds that the predictor variables of compatibility, security are significant and critically direct to the users’ intentions to adopt big data technology. The results indicate that the model is suited for studying users’ intentions to adopt Big Data technology in educational organizations. This study can help the Malaysian ministry of education to emphasize the important factors in further developing the use of Big Data technology in organizations. The findings provide important recommendations and implications for BDA technology practitioners and application developers, which could coincide with successful BDA technology deployment. This study provides practitioners with practical recommendations for guidance in incorporating and endorsing BDA activities in their organizations in order to maximize the benefits of revolutionary technology, particularly in government agencies.

The purpose of this study is to describe the Foreign Direct Investment (FDI) determinants of 6 countries, each of which is 3 countries from Southeast Asia and South Asia. Foreign Direct Investment (FDI) shows capital flows in 6 countries (Indonesia, Philippines, Malaysia, India, Pakistan and Bangladesh) that are affected by inflation, wage, Exchange Rate, Market Size and Trade Openness. The research method used is the regression of panel data for the period 2004-2019 from 6 countries in Southeast Asia obtained from the World Bank database. The results showed simultaneously and partially variable wage, exchange rate, market size and trade openness had a significant relationship with FDI inflows, except for variable inflation at α = 10%. Of the several variables studied, the dominant variable affecting the inflow of FDI in a country is the size of the market and followed by the wage level. In addition, of the 6 countries studied by countries that have great potential as recipients of FDI is Philippines.

This paper proposes a new method on ranking fuzzy numbers through the process of defuzzification by using maximizing and minimizing set on the triangular fuzzy numbers formed from generalized trapezoidal fuzzy numbers. In this method, a total utility value of each fuzzy number is defined by considering two left and two right utility values along with decision maker’s optimism which serves as a criterion for ranking fuzzy numbers and overcomes the limitations of Chen's (1985) [Chen, S. H. (1985). Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy Sets and Systems, 17(2), 113-129] ranking method.

This paper aims to contribute to the debate on the effect of board characteristics on firm performance. We use marginal q to estimate the effect of board characteristics on investment performance. Using data of 1616 firms that traded on the Standard and Poor´s (S&P) 1500 between 1997 and 2014, we use between and fixed effects estimators to capture the long-run effects and control other endogeneity problems as omitted variable bias. We find a negative and statistically significant effect of board size on investment performance. For the sample under study, we also find empirical evidence on the nonlinear relation between board independence and investment performance. Finally, using two different measures, we also find a nonlinear relation between board busyness and investment performance.

This paper deals with Flow-shop Sequence-Dependent Group Scheduling and worker assignment problem. Flow-shop allows the process of a set of families of products applying the group technology concept to reduce setup costs, lead times, and work-in-process inventory costs. The worker assignment problem deals with assigning workers to workstations considering their different abilities and learning effect. The proposed model in this paper considers different objectives. The decision problems in this cellular manufacturing system are the jobs scheduling within of own group, the group scheduling and the workers assignment to the machines. The aim of this paper is to consider a more realistic profile of heterogeneous workers introducing the learning effect in the joint group scheduling and workers assignment problem. A mathematical model and an evolutionary procedure has been developed to solve this problem. A benchmark of test cases having different numbers of machines, groups, jobs, worker skills and learning index, has been taken into account to compare the efficiency of the proposed algorithm with two well known procedures.

This article examines the nexus between Big data governance, dynamic capability and decision-making. Survey data was garnered from firms in Jordan and fuzzy sets (fsQCA) approach was applied. Fuzzy set configural modeling revealed two causal models for high decision-making effectiveness conditions. First, Big data governance, number of employees and firm age are necessary for higher levels of effective decision-making. Second, dynamic capability, number of employees and firm age are necessary for higher levels of effective decision-making. Insights for practitioners in an emerging economy and possible areas of future research are highlighted.

The purpose of this paper is to study the effect of the implementation of GCG principles and PSAK adoption of IFRS on quality of financial reports in SOEs. The data for the study comes from questionnaires collected by the survey method. Smart PLS 3.0 is an analytical technique used in research, with 99 people as the data. The results indicate that the implementation of PSAK adoption of IFRS and GCG principles had a substantial favorable impact on financial report quality.

This study aimed to develop a conceptual model of the mediating role of management accounting system (Broadscope) and organizational culture on the influence of mutual dependency and environmental uncertainty on managerial performance. The sample was 126 managers of Swamitra Palm Oil Plantation in Riau. The entire population was sampled. The data were processed using Structural Equation Modeling Partial Least Square (SEM PLS). The findings in this study are mutual dependency and environmental uncertainty have a positive influence on managerial performance, organizational culture mediates the influence of environmental uncertainty on managerial performance, meanwhile management accounting system (Broadscope) does not mediate the influence of mutual dependency on managerial performance.

Effective transshipment network is currently recognized as an important success determinant for most manufacturing organizations, because the transshipment management has significant impact on cost and environmental impact. Due to the complexity of the multi-criteria transshipment problem for infectious waste management (IWM) for this case, forty hospitals and three candidate disposal municipalities in Northeastern Thailand, a novel holistic approach (combination of fuzzy AHP, transshipment model and DEA) was developed for solving this problem. We first utilized the fuzzy AHP technique to calculate the location weights of each candidate disposal municipalities. Secondly, a new cost-based transshipment model was formulated and solved in order to provide the set of feasible solutions. These solutions can be viewed as decision making units (DMUs), inputs and outputs. Finally, DEA-CCR model was applied to calculate the efficiency scores of candidate DMUs. The study results demonstrated that the proposed holistic approach can help decision makers (DMs) to choose a suitable transshipment network for IWM. The major advantage of the proposed holistic approach is that both costs and environmental impacts under constraints are focused on simultaneously. Future work will apply the developed approach with other real-world complex problems to enhance the validity of the research output further. For large-size transshipment problems in which an exact solution cannot be found, meta-heuristics must be applied.