production and operations management
Maryam Rahimi; Roohollah Ghasemi; Ali Mohaghar
Abstract
In the competitive landscape of international markets, export performance is recognized as a key indicator of organizational success. Identifying the drivers that enhance this performance is therefore of critical importance. The present study examines the simultaneous effects of production capabilities ...
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In the competitive landscape of international markets, export performance is recognized as a key indicator of organizational success. Identifying the drivers that enhance this performance is therefore of critical importance. The present study examines the simultaneous effects of production capabilities and competitive strategies on export performance, with marketing capabilities considered as a mediating variable, in AmadehLaziz Company. This research is applied in nature and adopts a descriptive-correlational design. A stratified random sample of 320 respondents was selected. Data were collected using validated and reliable questionnaires, and analyzed through structural equation modeling. The findings indicate that production capabilities exert a direct influence on marketing capabilities. Competitive strategies also significantly reinforce marketing capabilities. Additionally, marketing capabilities directly affect export performance. Importantly, marketing capabilities serve as a mediating mechanism, such that production capabilities and competitive strategies indirectly shape export performance through marketing capabilities. However, the direct effects of production capabilities and competitive strategies on export performance were not statistically significant.
Industrial management
Bahareh Deljoo; Rohollah Ghasemi; Mohsen Moradi moghadam; Ali Mohaghar
Abstract
The food industry has been transformed by the Fourth Industrial Revolution, particularly through the application of the Internet of Things (IoT). This technology enhances efficiency by connecting various components of the factory—both wired and wirelessly—and paves the way for smart factories ...
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The food industry has been transformed by the Fourth Industrial Revolution, particularly through the application of the Internet of Things (IoT). This technology enhances efficiency by connecting various components of the factory—both wired and wirelessly—and paves the way for smart factories aligned with sustainability goals. The aim of this research is to analyze the capability–attractiveness of IoT applications in the food industry based on sustainability indicators and the readiness of selected companies in the food industry of Tehran province to implement these technologies. First, a systematic literature review was conducted to identify relevant IoT applications in the food industry, along with sustainability-based attractiveness indicators and capability criteria. The case study is selected companies in the food industry of Tehran province and their subsidiaries, which are currently deploying IoT technologies across various areas. Using the Best-Worst Method (BWM), the weights of the indicators were determined. Then, decision matrices were developed separately for evaluating the applications based on attractiveness (sustainability) and capability indicators, and each application was scored accordingly. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was then used to obtain final rankings. Based on the capability–attractiveness matrix, the most promising IoT applications identified for implementation in the company include “real-time data collection,” “inventory management and shelf replenishment,” “energy consumption management,” and “smart fire detection systems.” The findings offer valuable insights for identifying and adopting IoT applications in the food industry, considering the capacities and infrastructure of companies.
Introduction
The food industry, a fundamental sector for human needs, faces increasing demand, customer expectations, and intense competition. To ensure food safety and profitability, companies are adopting advanced technologies like the Internet of Things. IoT, through networks of sensors and smart devices, enables intelligent interaction between equipment, machinery, and information systems, enhancing efficiency, streamlining processes, and supporting sustainable development. The Iranian food industry faces challenges such as high food waste, weak supply chain traceability, inefficient resource management, and ongoing quality concerns. IoT can effectively address these issues, yet many companies have not fully adopted it. This research provides a systematic approach to examine and prioritize IoT applications based on sustainability attractiveness and the capability of active companies in Tehran province. The main research question is: What is the implementation priority of IoT applications in active companies in Tehran province based on the attractiveness of each application and the companies' capability to acquire this technology?
Research Background
The Iranian food industry confronts significant challenges that threaten its sustainability and competitiveness, including extensive food waste during production, storage, and distribution, weak traceability in the supply chain, inefficient management of critical resources such as water and energy, and persistent product quality and safety risks. Lack of effective infrastructure for tracking and verifying food authenticity reduces consumer trust and enables food fraud. In this context, IoT technology emerges as a modern and efficient solution. By employing smart sensors to monitor storage and transportation, tracking systems in the supply chain, real-time monitoring of raw materials and products, and wearable devices to enhance worker safety, IoT can increase productivity, improve food safety, reduce waste, and strengthen consumer confidence. Targeted IoT adoption can address structural problems and enhance Iran’s national and international food industry standing. Despite this potential, many companies have not yet fully embraced IoT. This research seeks to provide a systematic approach to examining and prioritizing IoT applications while considering their sustainability benefits and internal company capabilities.
Methodology
This applied research adopts a quantitative, descriptive-survey, and cross-sectional approach, utilizing both library and field methods for data collection. The initial phase involved a systematic literature review to identify IoT applications relevant to the food industry, along with sustainability-based attractiveness indicators and capability criteria. Through this process, twelve key IoT applications were identified, such as real-time data collection, smart fire detection systems, and energy management. Additionally, nine sustainability indicators were defined across economic dimensions—including operational cost savings—social dimensions, such as customer satisfaction, and environmental dimensions, like waste reduction. Furthermore, eight capability indicators were established, covering areas such as platform development, security, and regulatory compliance.
The study targeted experts from the food industry in Tehran province, all with a minimum of five years of experience in IoT-related projects. A judgmental sampling method was employed, and data were collected from seven selected experts. To determine the weights of the attractiveness and capability indicators, the Best-Worst Method (BWM) was applied. The experts completed BWM questionnaires, and the final group weights were derived by calculating the arithmetic mean of their responses. Consistency ratios were also computed to verify the reliability of the comparisons.
Following this, separate decision matrices were constructed to evaluate the twelve IoT applications based on the weighted attractiveness and capability indicators. Each application was scored by the experts using a 10-point Likert scale. The TOPSIS method was subsequently employed to process these matrices, yielding final scores and rankings for the applications according to each dimension.
Finally, a Capability-Attractiveness Matrix (ACM) was developed. The TOPSIS scores for attractiveness, represented on the vertical axis, and capability, on the horizontal axis, were plotted for each application. The mean scores of all applications served as cutoff points, dividing the matrix into four distinct quadrants and thereby enabling strategic prioritization of the IoT applications.
Findings
The BWM analysis revealed the relative importance of the indicators. For attractiveness, the economic dimension was the most critical (0.725), followed by the social (0.175) and environmental (0.100) dimensions. Among all sub-indicators, "operational cost savings" (EC1) had the highest final weight (0.494), underscoring its paramount importance. For capability, "IoT platform development" (CAP3) was the most significant indicator (0.305), followed by "application development" (CAP4) and "security capability" (CAP5). All consistency ratios were within acceptable limits, confirming the reliability of the expert judgments.
The TOPSIS analysis provided separate rankings based on attractiveness and capability. Based on attractiveness (sustainability benefits), the top applications were "real-time data collection" (A1), "inventory management" (A10), and "energy consumption management" (A11). Based on capability (ease of implementation), the top applications were "smart fire detection" (A2), "real-time data collection" (A1), and "energy consumption management" (A11).
The integration of the TOPSIS results into the ACM yielded the final strategic prioritization. The applications were categorized into four quadrants: Quadrant 1 (High Attractiveness, High Capability) contained the most promising applications for immediate implementation: A1 (Real-Time Data Collection), A10 (Inventory Management), A11 (Energy Management), and A2 (Smart Fire Detection). These represent the first priority. Quadrant 2 (High Attractiveness, Low Capability) included applications A5 (Operational Cost Control), A4 (Process Automation), and A8 (Remote Facility Control). They are desirable but require capability-building efforts, marking them as a second priority. Quadrant 3 (Low Attractiveness, High Capability) contained applications A6 (Quality Monitoring) and A7 (Worker Health Monitoring). While companies have the capability, the perceived sustainability benefits are lower. These could be developed after Quadrant 1 applications. Quadrant 4 (Low Attractiveness, Low Capability) included applications A12 (Supplier Tracking), A3 (Worker Tracking), and A9 (Environmental Monitoring), indicating the lowest priority for implementation.
Discussion and conclusion
This study identified and prioritized IoT applications for the food industry in Tehran province using a structured Capability-Attractiveness framework. The findings indicate that the primary focus for companies should be on applications in Quadrant 1, which offer high sustainability benefits and align with existing organizational capabilities. The prominence of real-time data collection, inventory management, and energy management aligns with global trends emphasizing operational efficiency and resource optimization.
The placement of environmental monitoring (A9) in the low-priority quadrant (4) contrasts with international research that emphasizes green technologies. This discrepancy may be attributed to weaker environmental regulations, lower technological infrastructure, or a primary focus on immediate economic gains within the Iranian context.
The prioritization based on the ACM provides a more comprehensive strategy than ranking by attractiveness or capability alone. It allows decision-makers to select applications that not only offer high value but also have a lower implementation risk, considering their specific resources and infrastructure.
In conclusion, this research enhances our understanding of IoT as an emerging and transformative technology in the food industry. It assesses various applications from economic, social, and environmental perspectives while evaluating implementation feasibility. The results can serve as a valuable guide for decision-makers and policymakers in the Iranian food industry, enabling a more strategic and effective adoption of IoT technologies. A limitation of this study is the lack of a detailed technical-economic feasibility analysis for each application. Future research should conduct in-depth studies on the selected applications to identify implementation challenges and provide practical solutions.
project management
ali mohaghar; Fatemeh Saghafi; Ebrahim Teimoury; Jalil Heidary Dahooie; Abdolkarim sabaee
Abstract
The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. ...
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The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. Construction supply chains are intricate systems, where the final performance results from numerous decisions made across multiple independent companies. Interactions among supply chain stakeholders and the unique characteristics of each project create complex phenomena with multiple interconnected elements and variables. The Viable System Model (VSM), rooted in organizational cybernetics, provides a structured approach to addressing complex and unstructured problems. This structured approach allows analysts to gain in-depth insights into the functional issues of the existing system and understand how to modify the system design to adapt to internal and external disruptions.MethodologyDespite the extensive capabilities of the Viable System Model as a diagnostic tool for assessing organizational structure and achieving viability, a systematic and distinct methodology for its application is lacking. Researchers in VSM often do not employ a specific methodology for systems analysis. In this study, we propose a methodology for applying the VSM as a diagnostic tool for organizations, derived from a review of theoretical foundations and practical requirements of VSM. Building on Jackson's methodology outlined in his book "System Thinking, Creative Holism for Managers," we have developed a methodology by integrating Jackson's approach with case study research. This methodology includes stages such as designing a diagnostic framework, selecting case studies, identifying systems, conducting system diagnosis, and validating the model. We applied this methodology to diagnose the supply chain of an Iranian petrochemical construction project, resulting in the development of a viable system model. The validity of the research methodology and findings was confirmed through expert participation and the application of multiple qualitative criteria.ResultsFollowing the selection of a case study and the identification of systems, we investigated the existence and function of five subsystems and communication channels within the focal system using a case study approach to gather information and develop the viable system model. Data was collected through semi-structured interviews conducted at various managerial and technical levels within a prominent project-oriented company in Iran's petrochemical industry. These interviews lasted between 45 and 60 minutes each. Data collection methods also included observation and document examination. The research involved a semi-structured interview with 18 individuals to explore complications within each of the five systems. Subsequently, the collected data was adapted to the model's requirements, and findings were extracted through intra-case analysis and coding. This process led to model development and the identification of weaknesses within the construction supply chain from the perspective of the five systems and communication channels, with a focus on achieving viability.ConclusionsThe developed model highlights weaknesses and bottlenecks within the focal system, shedding light on the most significant issues. A critical issue identified in the case study is the evident lack of coherence within System 4 and System 5. The results reveal that the incoherence of System 5, divided between parts of the company at level 0 and the parent company at a higher recursion level outside the focal system, results in defects within the communication channels related to this system, including C14 (Connection of System 4 with System 5), C9 (Algedonic channel), and C16 (Connection of System 5 with the homeostatic loop of Systems 3 and 4). Additionally, System 4, which is jointly managed by a segment of the company and the project management consultant, leads to disruptions in channels related to this system, particularly C13 (Homeostatic loop between Systems 3 and 4), C14 (Communication between System 4 and System 5), and C15 (Homeostat of System 4 with the future environment). Concerning common errors, the dominant error is E5, attributed to the lack of coherence between Systems 4 and 5 and the weak performance of System 2. This error largely stems from inconsistencies between the two operational units responsible for the engineering phase and the construction and installation phase. To achieve viability within the focal system, several measures should be taken, including the establishment of centralized Systems 4 and 5 within the company and strengthening communication channels with incomplete or insufficient capacity. These channels include the connection between System 4 and System 5 (C14), the Algedonic channel (C9), the connection of System 5 with the homeostatic loop of Systems 3 and 4 (C16), the homeostatic loop of System 3 and System 4 (C13), and the homeostat of System 4 with the future environment (C15). A crucial homeostatic link involves the communication and interaction between System 3 and System 4 (C13) to establish dynamic communication between the current project environment and its future. However, the interaction between these two systems is currently conflicting and misaligned due to the lack of coherence within System 4 and differences in functionality between System 3's perspective on the current state and System 4's perspective on the future state. Balancing the emphasis on System 4 and the future with the daily operations of the supply chain's operational units within System 1 is essential to avoid supply chain disruptions or inefficiencies. The lack of coherence within System 4 also affects the performance of other systems, particularly System 5, as well as the stability of System 4 in relation to the future environment. Inadequate information about the future environment can hinder informed decision-making within the system. By addressing these points within the model, the construction project's supply chain can move toward viability and better adapt to changes in the project environment. This research represents one of the limited studies in the implementation of VSM within the construction project environment.
Ali Mohaghar; Sara Aryaee; Jalil Heidary; Ara Toomanian
Abstract
Nowadays banks, credit and financial institutions are trying to increase profits, reduce costs, compete with rivals, attract customers and increase productivity. One of the factors that contributes to the implementation of these strategies is the optimum locations of branches. Locating the new branches ...
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Nowadays banks, credit and financial institutions are trying to increase profits, reduce costs, compete with rivals, attract customers and increase productivity. One of the factors that contributes to the implementation of these strategies is the optimum locations of branches. Locating the new branches of Mehr Eghtesad bank in the region 1 in Tehran city is the aim of this research. Since the focus of service centers such as banks is on maximal or full service to customers, among the all the covering models, Maximal Covering Location model is chosen as the best option to locate the new bank branches. To this end, related literature about locating bank branches, Geographical Information system (GIS) and maximal covering location problem (MCLP) examined. Then, through library Studies and interviewing with managers and experts, the researcher chose effective criteria and sub criteria for locating bank branches. The weights of criteria and sub criteria were determined through filling the questionnaires by managers. GIS used to extract some input data for the model and weighted maximal covering model (MCLM) with partial covering used to choose the best locations. Mathematical programming model formulated with 363 binary variables, 122 constraints, 121 demand areas, 121 potential points, the 1000 m buffer, α = 0.75, b = 50%, θ = 2 and s= 8 & 30 branches (with two different scenarios) and solved with GAMS optimization software. It is clear that by solving the first scenario, eight suitable locations and second scenario thirty suitable locations to open new branches will be generated.
Ali Mohaghar; Ali Morvoti Sharifabadi; Seyed Abdolaziz Yonesifar
Volume 9, Issue 24 , March 2012, , Pages 1-22
Abstract
In this article we try to collect all opinions of previous researchers in agility evaluation field and to provide a new method for evaluating agility by using Fuzzy logic. First, the structure’s agility level is evaluated by using FAI method. Due to the ranking Fuzzy numbers’ role and importance ...
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In this article we try to collect all opinions of previous researchers in agility evaluation field and to provide a new method for evaluating agility by using Fuzzy logic. First, the structure’s agility level is evaluated by using FAI method. Due to the ranking Fuzzy numbers’ role and importance in making decisions, then the Fuzzy numbers are ranked by using central gravity point technique and Topsis. In fact, this leads to identifying those factors which caused the structure agility reduction. This method would help managers in making decisions.
