Structural Modeling Approach Research Articles

Exploring 200 years of U.S. commodity market integration: A structural time series model approach

This paper uses a structural time series model to explore U.S. commodity market convergence, efficiency, and intertemporal smoothing from 1750–1949. I find near-continuous convergence that is largely concentrated in the frontier, broad antebellum efficiency gains, and intertemporal smoothing from the 1880s onward among the most perishable goods. The results reveal new periods of integration across all three metrics and underscore the rapid rate of integration on the frontier.

Supply Chains and Corporate Social Responsibility Orientation: An Interpretive Structural Modeling Approach

Corporate social responsibility (CSR) operations are becoming increasingly important for businesses throughout the world. It is critical to understand how stakeholders perceive these actions to achieve the intended CSR advantages. The nature of CSR motivation has been extensively discussed, yet there are still gaps in the literature, including CSR orientation. Individual enterprises are no longer pitted against one another in modern global competitiveness; instead, a company’s supply chains (SCs) are opposed to those of its competitors. To be competitive, SC partners must be aware of stakeholders’ expectations, which are increasingly focused on sustainable practices. Apart from financial performance, organizations are increasingly held liable for the environmental and social impacts of not just their own operations, but also the operations of their whole SCs, which may include second, third, or higher-tier suppliers. As a result, from raw material extraction through product recycling, an integrated approach to SC management necessitates the development and maintenance of relational capacities across SC partners. In SC collaborations, a company’s commitment to CSR can be a critical aspect. Managing CSR becomes more difficult as SCs get more sophisticated and multitiered, and it attracts greater attention. In this paper, the key drivers that shape CSR orientation are identified based on the literature and are classified into three categories: internal, external, and SC related. A conceptual model is formulated using interpretative structural modeling and MICMAC to identify interrelationships among these drivers, based on the opinions of experts from the Greek market and academia.
 Keywords: supply chain, corporate social responsibility, drivers, interpretive structural modeling, Greece

Has the COVID-19 pandemic impacted the intentions of individuals for a business venture? An integrated structural model approach

ABSTRACT This article provides distinctive insights into the main antecedents of entrepreneurial intention (EI) during the COVID-19 pandemic, merging Ajzen’s version of the Theory of Planned Behavior with an adjusted version of Shapero & Sokol’s Entrepreneurial Event Model, as well as an extended EI model developed by Krueger. Using a sample of 402 university students and applying structural equation modeling, the results identified attitudes toward entrepreneurship, perceived desirability and feasibility, and perceived self and collective efficacy as key drivers of EI, while capturing the turbulent investigation period through its impact on exogenous determinants, mainly the university environment.

Green organizational culture in manufacturing SMEs: an analysis of causal relationships

PurposeThe concern for environmental sustainability has created the need for businesses to embrace new environmentally responsible behavior, values and beliefs. Developing green culture has the capability of influencing employee attitudes and behavior and instilling certain values that shape an internal culture. The purpose of this study is to understand the causal relationship between the factors that influence green organization culture (GOC) in manufacturing small and medium manufacturing enterprises (SMEs) since they are considered significant contributors to environmental pollution. The study also aims to execute the driving and dependency power analysis to find the most and least significant factors of GOC.Design/methodology/approachThe study identified eight factors through an extensive literature review and validated them with the specialists. The total interpretive structural modeling (TISM) approach was employed for discovering the interaction among the identified factors and developing their structural hierarchy. Further matriced impact croises multiplication applique (MICMAC) analysis was carried out to determine the driving-dependence power of each factor.FindingsThe study discovered that the factors namely “Top management commitment and support towards green practices and workforce greening F(2)”, “Internal regulatory forces towards the environmental system (F3)” and “Organization's mission including environmental concern (F6)” were observed to be the most significant ones. “Environment that creates green work-life balance F(8)” and “Environment that promotes green attitude and behavior F(4)” were identified to be extremely dependent on the remaining factors.Research limitations/implicationsThe proposed outline has been established in the context of India and is restricted to manufacturing SMEs. The methodology presented in the study relies solely on experts' opinions which are qualitative in nature. Integration with a different method can be used to do statistical validation and add new variables to the problem, thereby reducing restrictions. The findings may facilitate manufacturing SME owners/managers and HR managers to recognize the most and least important factors of GOC and their causal relationships. This will increase awareness of GOC practices among managers thus contributing to environmental performance.Practical implicationsIt is essential for manufacturing small and medium enterprises to enhance their GOC for reducing its negative impact on the environment and further for gaining competitive advantage. Also, this research will offer insights into environmental management and enlarge awareness in the subsequent fields: of academics, practitioners and decision-makers who are engaged in managing environmental issues at various stages.Originality/valueThe researchers believe that the study is highly significant for manufacturing SMEs as they contribute to the economy as well as environmental degradation. Also, none of the research focused on understanding the causal relationships between the factors of GOC using the TISM approach in the Indian manufacturing SMEs context. This research adds an important contribution to the current GOC literature.

Moderate Alcohol Consumption and Depression: A Marginal Structural Model Approach Promoting Causal Inference.

Moderate alcohol consumption is associated with decreased risk for depression, but it remains unclear whether this is a causal relationship or a methodological artifact. To compare the effects of consistent abstinence and occasional, moderate, and above-guideline alcohol consumption throughout early to middle adulthood on depression at age 50, the authors conducted a secondary analysis of the National Longitudinal Survey of Youth 1979 cohort and employed a marginal structural model (MSM) approach. Baseline was set at 1994, when individuals were ages 29-37. The MSM incorporated measurements of alcohol consumption in 1994, 2002, and 2006, baseline and time-varying covariates, and repeated measurements with the Center for Epidemiologic Studies Depression Scale-Short Form (CES-D-SF). A total of 5,667 eligible participants provided valid data at baseline, 3,593 of whom provided valid outcome data. The authors used all observed data to predict CES-D-SF means and rates of probable depression for hypothetical trajectories of consistent alcohol consumption. The results approximated J-curve relationships. Specifically, both consistent occasional and consistent moderate drinkers were predicted to have reduced CES-D-SF scores and rates of probable depression at age 50 compared with consistent abstainers (CES-D-SF scores: b=-0.84, 95% CI=-1.47, -0.11; probable depression: odds ratio=0.58, 95% CI=0.36, 0.88 for consistent occasional drinkers vs. abstainers; CES-D-SF scores: b=-1.08, 95% CI=-1.88, -0.20; probable depression: odds ratio=0.59, 95% CI=0.26, 1.13 for consistent moderate drinkers vs. consistent abstainers). Consistent above-guideline drinkers were predicted to have slightly increased risk compared with consistent abstainers, but this was not significant. In sex-stratified analyses, results were similar for females and males. This study contributes preliminary evidence that associations between moderate alcohol consumption and reduced risk for depression may reflect genuine causal effects. Further research using diverse methodologies that promote causal inference is required.

Survival and sustenance strategy of primary agricultural cooperative credit societies in India: a fuzzy interpretive structural modelling approach

PurposePrimary agricultural cooperative credit societies (PACSs) in India are considered to be the backbone of the last mile delivery of rural credit for landless and marginal farmers and the poorest sections of the society. Contribution of PACS in social welfare is well documented. However, in spite of being such important form of organization at the grass root level, the authors find a typical baffling phenomenon which is fluctuating growth of PACS. Given that PACS have not been able to establish a consistent growth rate, thus hindering its trajectory to become a strong and consolidated organizational form, it is natural to investigate and identify those success factors that are critical for a newly formed PACS to survive and sustain. Hence it is necessary to undertake a strategic assessment of the function of PACS and hence identify those critical success factors (CSFs). This paper aims to address this issue.Design/methodology/approachThe authors review the existing literature and conduct interview with experts and other stakeholders with the purpose to gain a view of the strategic situation of PACS in India, especially with respect to their birth and death processes and identify a set of factors that are critical to the survival and sustenance of PACS. Based on the inputs from the experts, we modelled the interrelationships amongst these CSFs using interpretive structural modelling (ISM). Further, fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analysis is performed to cluster these CSFs into four quadrants based on their influence and dependence in the system.FindingsThe findings point out that a hierarchical interconnected structure exists amongst the CSFs that influence the survival and sustenance of the PACSs. “Quality and Motivation of Management” was found to be driving all other factors so far the survival of any PACS is considered. Also the authors have found that “Loan Recovery” is the most sensitive factor that needs to be taken care of for the sustenance of PACS. These findings are in the expected line and commensurate with the conventional wisdom yet to be documented till date.Originality/valueIt is a forward-looking analysis that tries to find out the CSFs for the survival of PACS in order to face the changing economic scenario of India which is still agrarian in nature. Both in terms of research question as well as methodology, to the best of the authors’ knowledge, this is first of its kind so far PACS are concerned being one of the most important but neglected entities in India; so far the last mile rural agricultural credit delivery is concerned, this study will help the policy makers to develop a holistic viewpoint in relation to long term sustenance of PACS.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2022-0331

Barriers to big data analytics (BDA) implementation in manufacturing supply chains

Big data analysis (BDA) can increase the capability of supply chain analysis of manufacturing companies. Therefore, many manufacturing companies want to use BDA, but it has been seen that BDA implementation is difficult, especially in developing countries due to the existence of various barriers related to finance, government regulations, etc. This paper aims to investigate the barriers to BDA implementation in Iranian companies. In literature, limited work has been done on identifying barriers to implementing BDA in developing countries. In this regard, 34 barriers were identified to BDA adoption in Iran by employing a literature review and feedback received from experts. Then, the most important barriers (14) were analyzed using integrated Interpretive Structural Modeling and MICMAC approach. Results show that two barriers; namely, lack of sufficient knowledge of senior managers and weakness of governance policies, are the most significant. Finally, crucial policy measures and recommendations are proposed to assist managers and government bodies.

Development of delay mitigation measures in construction projects: a combined interpretative structural modeling and MICMAC analysis approach

Construction delays are recurrent worldwide, regardless of the type of work, and can result in severe impacts, such as time and cost overruns and conflicts. This work aims to present a methodology to develop mitigation measures for the causes of Delays in Construction Projects (DCPs). Prior works have explored strategies to develop these measures but systematically failed to consider that the interrelationships among causes affect the significance of the impact of each cause. The methodology proposed combines the Interpretative Structural Modelling (ISM) and Matrix Cross Impact Matrix Multiplication (MICMAC) analyses approaches and is grounded on the opinions of construction experts collected during Focus Group Interviews (FGI). First, the critical causes of DCPs are identified. Second, the ISM model is built, representing the interrelationships between the causes and their hierarchy. Third, the MICMAC analysis is performed, revealing the strengths of the relationships among the influencing causes. Fourth, mitigation measures are developed to address the root causes identified in the previous steps, but they are designed to target and mitigate other causes, given their hierarchical relationships, driving power, and levels of dependence. Applying this methodology to the Portuguese context revealed 16 critical causes, which were then hierarchized into six levels of influence. Inadequate bidding and contract award processes and deficient communication between parties were deemed root causes, and 23 measures were put forward to mitigate DCPs. Therefore, this study contributes to the body of knowledge by designing an innovative and practitioner-wise methodology to develop mitigation measures in relation to DCPs and revealing some measures for the Portuguese context.

Exploring the relationship between social media knowledge platform (SMKP) using smart devices and the impact on students’ academic performances

This research study is an attempt to investigate and recommend the applications and usefulness of social media as a knowledge sharing platform using smart mobile devices and students’ academic performances. Research literature reveals that further examination of this idea is a must as it is increasingly becoming an integral part and a current mandate for digital-era learners. This study is exploratory based on learners’ data which includes students from foundation, junior and senior courses at a university. The objective was to cognize learners’ perceptions on collaborative learning while using applications of social media knowledge platform and smart mobile devices. Structural Model approach is followed to validate the data and undertake the required analysis. The resulting analysis shows that a significantly positive relation exists between the available platforms of knowledge applications using smart devices and its substantial impact on students’ overall performances. In addition, it could be observed that generally students have positive and valuable perception on the use of social media knowledge platform and smart mobile devices in collaborative learning settings. Moreover, such settings encourage students-students’ interactions, studentsteachers’ interactions, and the growing trends of students to online experts’ interactions. Furthermore, it was noticed that these interactions improve students’ engagement with such platforms using smart devices, which consequently has significant positive impact on students’ academic performances. The findings propose the inculcation in students the positive role of the use of social media knowledge platforms using smart devices so to encourage collaborative learning, to enhance active learning, to be more dynamic & engaging, to broaden their domain-knowledge, and to promote academic researchoriented learning, which are all crucial for graduate employability.

Is the e-payment gateway system sustainable in India – Analysis through the interpretive structural model approach

Globally, digital payment has been seen as a common feature of developed countries. A gap was identified in literature regarding identification of the most critical variables in e-payment and the development of a model for the sustainability of e-payment. The purpose of the present study is to fill this gap, by identifying and modelling the critical factors influencing e-payment sustainability. The study also looks at the sustainability of the e-payment gateway system and develops the interpretive structural model (ISM) approach. The cross-impact matrix multiplication applied to classification (MICMAC) analysis technique has been used. Results of the study shows that behavioural intention, compatibility, trialability, trust, security, perceived cost and other factors play a significant role in the commitment of the consumer towards e-payment. The findings of the study will guide government, corporates and policy makers while framing strategies and policies for the sustainability of digital payment – a cashless move in India.

Designing an interpretive structural model of ecological literacy development challenges in secondary schools

Background and Aim: As the first and most important educational institution of the country, the school plays a decisive role in teaching ecological literacy along with other organizations and educational tools. The purpose of this research was to design an interpretative structural model of the challenges of developing ecological literacy in secondary schools. Methods: The current research is of mixed type (qualitative and quantitative). In the first phase, a qualitative research method was conducted using thematic analysis, and in the second phase, a quantitative method was conducted based on interpretive structural modeling. The statistical community in both qualitative and quantitative sections, due to the expert-centeredness of the interpretive structural modeling approach, formed experts, which included school principals, teachers, environmental education experts, environmental education professors, and environmental elites. They were selected purposefully and until theoretical saturation was reached (22 people). Sampling method in the quantitative part, due to the expert-oriented approach of interpretive structural modeling, the experts were in the qualitative part (N=20). The measurement tool in the qualitative part was a semi-structured interview and in the quantitative part, a questionnaire. Validity and reliability of the data were confirmed. Two methods of thematic analysis (Max QDI software) and Interpretive Structural Modeling (ISM) (Excel software) were used to analyze the data. Results: 6 main themes of ecological literacy development challenges in secondary schools have been identified, which include human, infrastructure, economic, attitudinal, curriculum and political challenges. Conclusion: Human challenge and curriculum are in the independent cluster, that is, it has a great influence on other factors and other factors have little influence on it; The themes of infrastructure and curriculum are placed in the dependent cluster, that is, they are affected by other factors and have little effect on other factors; Economic and attitudinal themes are placed in the linked cluster, that is, they both influence other factors and are influenced by other factors.

Modelling the Critical Success Factors of Net-zero Energy Buildings in India

Amidst the widespread consciousness and several awareness programs to combat the adverse impact of greenhouse gas emissions on the climate, Net-zero energy buildings (NZEB) have emerged as one of the potential solutions. Various factors, including the need for heavy initial capital investment, weather conditions, government regulations, policies, training and development, technology, and so forth, were figured out by carrying out a literature review and interviewing the area experts. Further, investigating the inter-contextual relationships helps to have key success factors of NZEBs in India that are multidimensional in nature. To achieve this goal, the Interpretive Structural Modelling (ISM) approach was employed to compute the mutual influence of the ten key success factors in the Indian context. The results report that favorable weather conditions, government policies, and regulations are the most crucial factors for the NZEB sectoral development in Indian contexts.

Modelling the interaction among the key performance indicators of sustainable supply chain from the perspective of perishable food

Sustainability of the supply chain is a research area of major concern in recent days. Due to rapid population growth globally, demand for food and nutrition is increasing day by day. So, sustainability in the food supply chain is essentially required to meet the ever-increasing demand. In this paper, 30 sustainable indicators have been identified from various literatures in the perishable food supply chain and sorted with the help of relevant field and academic experts. An interpretive structural modelling (ISM) approach has been applied to find out the interrelationship among the indicators. The level of importance of all the indicators have been analysed by using ISM and further utilised to develop models for assessing sustainability in the supply chain. The results of this study may be used as input to AHP, TOPSIS and other MCDM approach. MICMAC analysis has been applied to classify the sustainable indicators into four factors by using their dependence and driving power.

Interpretive Structural Modeling Based Assessment and Optimization of Cloud with Internet of Things (CloudIoT) Issues Through Effective Scheduling

Integrated CloudIoT is an emerging field of study that integrates the Cloud and the Internet of Things (IoT) to make machines smarter and deal with real-world objects in a distributed manner. It collects data from various devices and analyses it to increase efficiency and productivity. Because Cloud and IoT are complementary technologies with distinct areas of application, integrating them is difficult. This paper identifies various CloudIoT issues and analyzes them to make a relational model. The Interpretive Structural Modeling (ISM) approach establishes the interrelationship among the problems identified. The issues are categorised based on driving and dependent power, and a hierarchical model is presented. The ISM analysis shows that scheduling is an important aspect and has both (driving and dependence) power to improve the performance of the CloudIoT model. Therefore, existing CloudIoT job scheduling algorithms are analysed, and a cloud-centric scheduling mechanism is proposed to execute IoT jobs on a suitable cloud. The cloud implementation using an open-source framework to simulate Cloud Computing (CloudSim), based on the job’s workload, is presented. Simulation results of the proposed scheduling model indicate better performance in terms of Average Waiting Time (AWT) and makespan than existing cloud-based scheduling approaches.

Situational analysis and conceptual model development of crimes against women and children

Violence has existed in many forms in society whilst those against women and children have always been higher. The rate of occurrence of violence has been in an increasing trend over the last decade worldwide. The present study involves a detailed study on the impact of violence and the factors that contribute to violence. Situational analysis of the various forms of violence against women and children was studied in the state of Kerala, India. Several predominant factors across various levels of the socio-ecological model were identified and a conceptual model was developed using an interpretive structural modelling (ISM) approach. Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) plot revealed that the societal factors were the highly influencing ones. Individual-level factors placed themselves in the top-most level and as linkage variables. Suitable recommendations and implications based on the results of the conceptual model and the situation analysis are provided.

Analysis of the enablers of supply chain digitalisation in the electronics industry: an interpretive structural modelling approach

Supply chain digitalisation has great advantages. In spite of a large number of studies, there is a lack of literature to identify and address the key enablers to be considered for supply chain digitalisation. In this study, 13 key enablers for integration of supply chain through digitalisation in an electronic supply chain in Indian context are identified and shortlisted in consultation with the experts from industry and academia. Interpretive structural modelling has been used for understanding of the hierarchical and contextual influences among the identified key enablers for supply chain digitalisation. Results of the model indicate that prior to taking a decision on supply chain digitalisation, companies have to identify the key enablers and its impact on digitalisation process. Policy decision-makers could use the results of this study to identify the key enablers and their interrelationship for taking effective decision for supply chain digitalisation process.

Model of the linkage between land cover changes to water discharge and food productivity: The case of the Konaweha watershed in Indonesia

Changes in watershed land cover have an impact on reducing water discharge, as well as other derivative impacts such as the productivity of food crops, horticulture, and plantations. This study tries to offer a conceptual model of the effect of changes in watershed land cover, water discharge, and food productivity through food crops, horticultural crops, and plantation crops. This study uses a quantitative approach based on time series data between 2002 and 2021. Data is analyzed using a structural model approach with SEM-SmartPLS software. As a result, changes in land cover have a significant effect on water discharge, but they have no effect on food productivity. Water discharge has a significant effect on food production, and changes in land cover greatly affect food productivity through the role of intermediary variables (mediation) of water discharge. In 2041, changes in land cover can reduce water discharge by around 47.9%. Then the water discharge is estimated to have an impact on the productivity of food crops by 62.3%, vegetable productivity by around 45.7%, and plantation crop productivity by around 72.7%.

Interpretive Structural Model Approach to Mobile Banking Adoption in a Rapidly Growing Economy: a Banking Expert's Perspective

Interpretive Structural Model Approach to Mobile Banking Adoption in a Rapidly Growing Economy: a Banking Expert's Perspective

Facilitators of modularity in healthcare services: An interpretive structural modeling approach

The purpose ofthis paper is to perform structural analysis of facilitators of modular architecturein healthcare services by applying interpretive structural modeling (ISM).Inputs were taken from healthcare industry experts and academicians inidentifying and understanding interdependencies among facilitators of modulararchitecture in healthcare services. Further these interdependencies arestructured into a hierarchy in order to derive structural models to deliveruseful insights for theory and practice. Using the ISM approach the facilitatorsof modularity in healthcare services were clustered according to their drivingpower and dependence power. Patient centricity is at the bottom level of thehierarchy implying highest driving power and requires higher attention todeliver quality care outcomes. Facilitators like value dense environment, knowledgeand competence, goal alignment and le-agile strategies have medium driverand dependence powers. The study added insights to the theory of modularsystems. Theauthors recognize that modularity helps in enhancing the patientcentric orientation. The findings provide potentially important information tohealth service managers and providers, enabling them to understand therequisites of modular architecture. This is the first study exploring therelationships between facilitators of modularity in healthcare services. Thestudy complements literature on service modularity with reference to specializedcare unit of maternity services.

Evaluating Additive Manufacturing Success Factors for the Aviation Industry: An Interpretive Structural Modelling Approach

Evaluating Additive Manufacturing Success Factors for the Aviation Industry: An Interpretive Structural Modelling Approach