International Journal of Industrial Engineering and Productional Research
Volume:34 Issue: 4, Dec 2023

This study delves into modelling criteria for product returns within the context of a pharmaceutical company. It aims to address the main issues surrounding product return, investigate the factors that contribute to the criteria for product return, and provide recommendations for improving the process. Feedback from 170 participants was collected and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The study's findings demonstrate the significance of various factors in shaping the criteria for product returns in the pharmaceutical industry. These factors include product quality, safety concerns, expiration dates, sales performance, and regulatory compliance. The analysis emphasizes the importance of establishing positive and significant relationships among direct, mediating, and moderating variables to determine the criteria for product returns effectively. Based on the results, it is recommended that the pharmaceutical industry concentrate its efforts on strengthening the pharmaceutical supply chain, fostering trust with customers, and contributing to the long-term growth and sustainability of the sector. By prioritizing these areas, pharmaceutical companies can enhance customer confidence, facilitate the expansion and sustainability of the industry, and capitalize on opportunities within the pharmaceutical market. Overall, the outcomes of this study provide valuable insights into modelling criteria for product returns in a pharmaceutical company. Implementing the recommended strategies will improve customer satisfaction and support the overall success and development of the pharmaceutical sector, enabling businesses to thrive in the industry's dynamic landscape.

This research aims to identify the initial OEE (Overall Equipment Efficiency) values on automated packaging machines with a 2d barcode track and trace system. Quantitative research methods used to obtain the OEE value, analysis of factors affecting the OEE values, developing a strategy to make improvements, and evaluate these strategies on the level of machine productivity. The results showed that the OEE value of the automatic packing machine with 2d barcode track and trace system was 30.49%. The value is still far below the company’s standard of 85%. Availability (av) and the rate of quality (rq) are quite high. However, the performance rate (pe) is still low until the OEE value is low. Based on six big loss analysis, the biggest loss that leads to low OEE value is decreasing speed. Machine is operated at speeds that do not match design (ideal); usually, the real speed is lower than the ideal speed, that can be caused by small product batch sizes. Based on average OEE after a problem solving of 67.67 %. An increase in value gained by 37.18 % of previous achievements. To sum up, this study contributes to the development of best practices and strategies for optimizing machine productivity and improving overall equipment effectiveness in various manufacturing contexts.

The lighting of the work environment and its quantitative and qualitative characteristics, such as the intensity of the light and the color temperature, as a physical characteristic, have a great impact on the mental health, behavior and performance of people. The physical factors of the work environment, the personality type and behavioral characteristics of people are effective in their efficiency and productivity.

In this study, 35 male students of Tarbiat Modares University were studied. This study was designed in 3 locations with different lighting systems of LED lamps with color temperature of 3000, 4000 and 5000 degrees Kelvin. Stroop test software was used to check cognitive activities and Neo questionnaire was used to determine personality type.

The results showed that the average reaction time when facing the LED lamp with a color temperature of 4000 degrees Kelvin in the group of consonant words is the lowest (average response time 601.22 milliseconds), the lowest amount of errors in the group of consonant words and at a color temperature of 5000 degrees Kelvin observed (average number of errors 2.71).

The results of this study showed that the LED lighting system with high color temperature can be effective on people's cognitive performance by reducing errors and increasing attention and reaction time. In order to improve people's cognitive performance, it is suggested to use lighting system with high color temperature in sensitive places.

In this paper, the modeling of a make-to-order problem considering the order queue system under the robust fuzzy programming method is discussed. Considering the importance of timely delivery of ideal demand, a four-level model of suppliers, production centers, distribution centers, and customers has been designed to reduce total costs. Due to the uncertainty of transportation costs and ideal demand, the robust fuzzy programming method is used to control the model. The analysis of different sample problems with LCA, PSO, and SSA methods shows that with the increase in the uncertainty rate, the amount of ideal demand has increased and this has led to an increase in total costs. On the other hand, with the increase of the stability coefficients of the model, contrary to the reduction of the shortage costs, the total costs of the model have increased due to transportation. Also, the analysis showed that with the increase in the number of servers in the production and distribution centers, the average waiting time for customers' order queues has decreased. Because by reducing the waiting time, the total delivery time of customer demand decreases, and the amount of actual demand increases. On the other hand, due to the lack of significant difference between the OBF averages among the solution methods, they were prioritized and SSA was recognized as an efficient algorithm. By implementing the model in a real case study in Iran for electronic components, it was observed that 4 areas of the Tehran metropolis (8-18-16-22) were selected as actual distribution centers. Also, the costs of the whole model were investigated in the case study and the results show the high efficiency of the solution methods in solving the MTOSC problem.

Prediction of unexpected incidents and energy consumption are some industry issues and problems. The present study addressed the single machine scheduling with preemption and considering failures. This study also aimed at minimizing earliness and tardiness penalties and job expansion and compression. The present study presented a mathematical model for this problem by considering processing time, machine idle, release time, rotational speed and torque, failure time, and machine availability after repair and maintenance. The failure time has been predicted using a machine learning algorithm. The results indicate that the proposed model is useful for problems with 6-job dimensions. This study solves this problem in two parts. The first part predicts failures and obtained some rules to correct the process, and the second includes the sequence of single-machine scheduling operations. In the second part, the scheduling model was used considering these failures and machine idle in single-machine scheduling to achieve an optimal sequence, minimize energy consumption, and reduce failures.

Purpose – This study aims to identify and classify the most relevant works in the social presence literature to provide insight into the most promising research areas and global research trends and to help future researchers find the most relevant information based on their research interests.

Design/methodology/approach – The study provides a bibliometric analysis of 1962 journal articles published between 1958 and 2022 based on publication outputs, co-authorships among authors and affiliated countries, and co-occurrences of author keywords referenced in the Scopus database.

Findings – There has been a steady increase in the cumulative number of publications between 2014 and 2018, with an increase of 100 articles per year. Over 55% of the total publications worldwide were contributed by researchers from China and the United States. In addition, four of the most productive universities in each of the 15 leading countries are ranked among the world's top 100 universities.  Research on social presence addresses some interesting topics such as e-learning, social media, computer-mediated communication (CMC), and community of inquiry (CoI).

This bibliometric analysis was conducted to identify trends in the area of social presence. As a result of this study, the publication global trend was identified, which is likely to continue to increase in the future. Co-authorship and co-occurrence analyses were also performed to evaluate the countries that are leading the way as well as keywords used in the literature.

[ DOI: 10.22068/ijiepr.34.1.4 ]









 









 [ Downloaded from ijiepr.iust.ac.ir on 2023-06-21 ]




Software testing is the process of assessing the functionality of a software program. The software testing process checks for inaccuracies, gaps and whether the application outcome matches desired expectations before the software is installed and goes into production. Normally in large organizations, the development team allocates a high portion of estimated development time, cost and efficiency for regression testing to assure software testing quality assurance. The quality of developed software relies upon three factors time, efficiency and testing technique used for regression testing. Regression testing is an important component of software testing and maintenance, taking up a significant share of the total testing time, efficiency and resources organizations use in testing techniques. The key to successful regression testing using Test Case Prioritization (TCP), Test case Selection (TCS) and Test Case Minimization (TCM) is maximizing the test cases' effectiveness while considering the limited resources available. Regression testing introduced numerous techniques for (TCP, TCS, TCM) to maximize the efficiency based on Average Percentage Fault Detection (APFD). In recent studies, the TCP and TCS techniques can give the highest APFD score. However, each TCP and TCS approacshow limitations, such as high execution cost, time, efficiency, and lack of information. TCP and TCS approaches that can cover multiple test suite variables (time, cost, efficiency) remained inefficient. Thus, there is a need for a hybrid TCP and TCS technique to be developed to search for the best method that gives a high APFD score while having good coverage of test cases relevant to the cost and execution time to improve efficiency. The hybrid technique aims to define an ideal ranking order of test cases, allowing for higher coverage and early fault detection with reduced test suite size. This study reviews TCP and TCS hybrid techniques to reduce testing time, cost and improve efficiency for regression testing. Each TCS and TCP technique in regression testing has identified apparent standards, benefits, and restrictions.

This research aims to determine the scope and pattern of research and understand trends in class-based storage research, to deliver the latest research on the topic of class-based storage for future studies.  This study is based on data derived from several journal publications, limited only to publication years of 2012 to 2023. Harzing's Publish or Perish and VOSviewer software were used in data collection. Therefore, 980 articles were obtained based on keywords and processed by using bibliometric analysis. From the results of bibliometric research on the topic of class-based storage, identification of trends and patterns on research growth is obtained, analyzing renewal, obsolescence, and distribution of references, estimating productivity, author, year of publication, most-contributed publishers, and collaboration among authors who discussing interrelated topics. This research shows that in bibliometric studies in class-based storage literature, by involving analysis through keywords contained in titles and abstracts, as well as various analyses of years of publication, most publications are able to deepen and expand the literature in the previous class-based storage-related research. So that the findings in terms of assessment techniques and relationships can be used as information for future researchers in such fields of study. Research on bibliometrics is the main reference, especially in the arrangement of facility layout and warehouse management. The originality provided by this study lies in the presentation of differences and similarities between current researchers and previous researchers and the processing of publication databases based on class-based storage journals. So that all published information on the topic of class-based storage in the last 10 years (2012-2023) could become a basis and reference for further research.

Online group buying emerged as one of the most successful online business models. Online group buying refers to the online buying community's purchase of products and services significantly reduced from the regular retail price. According to previous studies, many factors can affect purchase intention on such a platform. This study developed a model that explains the factors influencing purchase intention in an online group buying website, it also proposed a model to study online group buying sustainability from the customer perspective. It considers the impact of sustainability dimensions, customer satisfaction, and website quality on customers' intention to buy. This study examines three dimensions of social, economic, and environmental factors on customers' intention to buy from online group buying websites for the first time. This study also addressed the related relationship between the sustainability dimensions in such a platform. The results show that each social, economic, and environmental dimension positively affects customer satisfaction. Moreover, the sustainability dimensions positively influence the purchase intention, while the environmental dimension has less impact, and the studied online group buying customers pay less attention to it, also, the satisfaction and quality of the website affect the purchase intention.

The online marketplace offers abundant opportunities for businesses across various industries. Manufacturers are increasingly adopting online sales channels in addition to retail sales to bypass intermediaries, directly reach end users, and enhance profitability. To attract a larger customer base, manufacturers employ advertising across multiple channels, while retailers focus on local advertising within their respective regions. In this research, one of the key challenges revolves around determining pricing strategies and advertising investments for both manufacturers and retailers, while considering various constraints. The presented supply chain includes both global and local advertising, with the impact of global advertising being manifested through distinct advertising channels that are specified individually. To enhance retailer motivation, the manufacturer contributes to the cost of local advertising. To address these challenges, a bi-level model is formulated, and the concept of Variational Inequalities is employed to solve it. The experimental results are obtained and analyzed using Gams software.

Compared to coal and other fossil fuels, renewable energy (RE) sources emit significantly less carbon dioxide (CO2). In this sense, switching to such sources brings many positive effects to the environment through mitigating climate change, so the terms green energy and clean energy, have been derived from these constructive environmental impacts. Given the utmost importance of RE development, the primary objective of this study was to identify and prioritize the effective RE development strategies in Mazandaran Province, Iran, using different methods, including the Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, along with other decision-making techniques. Recruiting a team of 11 industrial and academic experts, the strategies to implement in this region were developed in line with the RE development plans. For this purpose, the Multi-Criteria Decision-Making (MCDM) methodologies were utilized within the gray fuzzy environment to manage the existing uncertainties. The Gray-Additive Ratio Assessment System (Gray ARAS) was further applied to rank the main factors at each level. According to the SWOT analysis and the Stepwise Weight Assessment Ratio Analysis (SWARA) outcomes, among the major factors shaping RE development in Mazandaran Province, Iran, the economic criterion, with the final weight of 0.24, was ranked first; and then the geographical and environmental criteria, having the final weights of 0.23 and 0.19, were put in the second and third places, respectively. In this regard, appropriate location, with the final weight of 0.226, was ranked first; and subsequently pollution reduction and energy production costs, receiving the final weights of 0.103 and 0.094, were the second and third sub-criteria, respectively. As a final point, the validation results based on the Gray-Weighted Aggregated Sum Product Assessment (Gray-WASPAS) and ranking obtained through the Gray-ARAS were confirmed.

In developing countries, Human Resources (HR) is considered one of the most important factors that lead to the improvement and successful organization of employee performance. Human Resources Management (HRM) practices play an effective role in this performance, as this is evident through the impact of talent management on HRM practices, which leads to increasing and improving the production process for employees and making them possess high quality. Given the importance of this topic, the current study aims to determine the impact of the moderating role of Talent Management (TM) on HRM practices, which include good training, recruitment, performance evaluation, and remuneration system, on the institutional performance (IP) of Jordanian pharmaceutical companies. The study population includes employees of 13 pharmaceutical companies listed on the Amman Stock Exchange in Jordan. A random sample of 250 employees was taken. An electronic questionnaire was sent to the employees via e-mail. The 216 valid questionnaires were found, and the response rate was 86%. Two approaches, descriptive and analytical, were used due to their suitability to the nature of this work. The results obtained indicated that there is a significant positive impact of HRM practices (recruitment, training, performance evaluation, and remuneration system) on IP in Jordanian pharmaceutical companies. In addition, it was found that there is a positive impact of the moderating role of TM on the relationship between HRM practices and IP in these companies. Our study recommends that HRM practices can be used as strategic tools to align with long-term goals, invest in high-potential employees, provide performance growth opportunities, and create a collaborative work environment.

Since 1952, when the mean-variance model of Markowitz introduced as a basic framework for modern portfolio theory, some researchers have been trying to add new dimensions to this model. However, most of them have neglected the nature of decision making in such situations and have focused only on adding non-fundamental and thematic dimensions such as considering social responsibilities and green industries. Due to the nature of stock market, the decisions made in this sector are influenced by two different parameters: (1) analyzing past trends and (2) predicting future developments. The former is derived objectively based on historical data that is available to everyone while the latter is achieved subjectively based on inside-information that is only available to the investor. Naturally, due to differences in the origin of their creation the bridge between these two types of analysis in order to optimize the portfolio will be a phenomenon called "ambiguity". Hence, in this paper, we revisited Markowitz's model and proposed a modification that allow incorporating not only return and risk but also incorporate ambiguity into the investment decision making process. Finally, in order to demonstrate how the proposed model can be applied in practice, it is implemented in Tehran Stock Exchange (TSE) and the experimental results are examined. From the experimental results, we can extract that the proposed model is more comprehensive than Markowitz's model and has greater ability to cover the conditions of the stock market.

Family-owned businesses are the backbone of many economies across the world. Growing expansion and globalisation have presented several obstacles to family enterprises. How you handle them can spell the difference between success and failure. In addition, some essential systematic evaluations have recognised that studies on listed family firms against unlisted family enterprises have attracted significant scholarly attention in the context of Interlocking Directorates and performance. This is a pity because unlisted family businesses account for a large share of the economic landscapes of both emerging and industrialised countries. The current study aimed to investigate the relationship between family ownership, board composition and performance of the family businesses. This study used the PRISMA statement 2020 to include and exclude the articles. In addition, we used the VOS viewer software to determine major classifications of data streams for the analysis. The results show that four significant research areas in prior research have been conducted, interlocking directorates, family ownership, board composition and performance of the unlisted firms. The findings indicate that interlock directors positively impact the firm performance of unlisted family firms. The unlisted firms showed a significant presence of board directors (which might have been due to their more excellent knowledge of the firm) with a subsequent positive effect on strategic planning decisions. It is also important to note the differences between family firms run by the first generation and those run by subsequent generations. The presence of independents and affiliates on the board positively affects performance when the first generation runs the firm. Moreover, our findings provide a new perspective on board directors’ role in the corporate governance of unlisted family firms.