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Article
Publication date: 13 August 2021

Mosayeb Dashtpeyma and Reza Ghodsi

This research paper aims to identify and evaluate the enabling factors of agility capability in humanitarian relief chain network.

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Abstract

Purpose

This research paper aims to identify and evaluate the enabling factors of agility capability in humanitarian relief chain network.

Design/methodology/approach

The research phases were implemented based on an integrated framework. First, a reference framework of the enablers has been constructed based on a literature review. Then, a hybrid evaluation approach is applied that combines fuzzy decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) to achieve reliable results. It provides a road map to identify and evaluate the interactions between the enabling factors and determines the weights correspond to their relative importance. This approach takes advantage of fuzzy set theory to deal with ambiguities, uncertainties and vagueness inherent in the evaluation process.

Findings

Relief chain agility is a vital determinant of the effectiveness to succeed humanitarian missions during and after natural and unnatural disasters such as earthquakes, epidemics and terrorist attacks. Results shed light on the essential enabling factors, relationships among them, and their importance for developing humanitarian relief chain agility enhancing the overall performance quality.

Originality/value

The integrated framework is implemented for the Red Crescent, a nongovernmental organization in Iran, which is trying to optimize the agility of their humanitarian relief chain network. In short, the findings are beneficial for identification and utilization of the essential prerequisites of agility in order to develop an agile humanitarian relief chain.

Details

International Journal of Emergency Services, vol. 11 no. 1
Type: Research Article
ISSN: 2047-0894

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Article
Publication date: 22 March 2021

Mirpouya Mirmozaffari, Elham Shadkam, Seyyed Mohammad Khalili, Kamyar Kabirifar, Reza Yazdani and Tayyebeh Asgari Gashteroodkhani

Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO2) into the atmosphere, resulting in adverse environmental…

757

Abstract

Purpose

Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO2) into the atmosphere, resulting in adverse environmental impacts and high energy consumption. Increasing demand for CO2 consumption has urged construction companies and decision-makers to consider ecological efficiency affected by CO2 consumption. Therefore, this paper aims to develop a method capable of analyzing and assessing the eco-efficiency determining factor in Iran’s 22 local cement companies over 2015–2019.

Design/methodology/approach

This research uses two well-known artificial intelligence approaches, namely, optimization data envelopment analysis (DEA) and machine learning algorithms at the first and second steps, respectively, to fulfill the research aim. Meanwhile, to find the superior model, the CCR model, BBC model and additive DEA models to measure the efficiency of decision processes are used. A proportional decreasing or increasing of inputs/outputs is the main concern in measuring efficiency which neglect slacks, and hence, is a critical limitation of radial models. Thus, the additive model by considering desirable and undesirable outputs, as a well-known DEA non-proportional and non-radial model, is used to solve the problem. Additive models measure efficiency via slack variables. Considering both input-oriented and output-oriented is one of the main advantages of the additive model.

Findings

After applying the proposed model, the Malmquist productivity index is computed to evaluate the productivity of companies over 2015–2019. Although DEA is an appreciated method for evaluating, it fails to extract unknown information. Thus, machine learning algorithms play an important role in this step. Association rules are used to extract hidden rules and to introduce the three strongest rules. Finally, three data mining classification algorithms in three different tools have been applied to introduce the superior algorithm and tool. A new converting two-stage to single-stage model is proposed to obtain the eco-efficiency of the whole system. This model is proposed to fix the efficiency of a two-stage process and prevent the dependency on various weights. Converting undesirable outputs and desirable inputs to final desirable inputs in a single-stage model to minimize inputs, as well as turning desirable outputs to final desirable outputs in the single-stage model to maximize outputs to have a positive effect on the efficiency of the whole process.

Originality/value

The performance of the proposed approach provides us with a chance to recognize pattern recognition of the whole, combining DEA and data mining techniques during the selected period (five years from 2015 to 2019). Meanwhile, the cement industry is one of the foremost manufacturers of naturally harmful material using an undesirable by-product; specific stress is given to that pollution control investment or undesirable output while evaluating energy use efficiency. The significant concentration of the study is to respond to five preliminary questions.

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Article
Publication date: 10 August 2012

Sayed Ali Siadat, Reza Hoveida, Mohammad Abbaszadeh and Leila Moghtadaie

The purpose of this paper is to provide a theoretical picture of the concept of knowledge creation and then investigate the effects on it of such variables as social capital and…

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Abstract

Purpose

The purpose of this paper is to provide a theoretical picture of the concept of knowledge creation and then investigate the effects on it of such variables as social capital and organizational culture.

Design/methodology/approach

The population of this study includes faculty members of the University of Isfahan (Iran) in 2008 (476 cases). From among these cases, 142 cases were selected based on the Cochran formula. Survey was used as the research method and a questionnaire was used for data collection. Pearson correlation “r” and multi‐variable regression were employed, and in the next stage, through drawing the model of structural equations, the direct effects, indirect effects and total effects of independent variables on the dependent variable were investigated, based on path analysis model. SPSS and LISREL were employed for statistical analysis.

Findings

The results revealed that social capital and organizational culture had meaningful effect on knowledge creation. The analysis showed that the independent variables mentioned above could determine 36 percent of the effects of the dependent variable.

Research limitations/implications

The findings are based, in the main, on an extensive, single university study; therefore it is necessary to be cautious about generalizing the result of this study to other universities in Iran.

Originality/value

The paper can contribute to organizations through providing a holistic picture of the role of knowledge creation in organizations (especially universities).

Details

Journal of Management Development, vol. 31 no. 8
Type: Research Article
ISSN: 0262-1711

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Article
Publication date: 7 November 2016

Nazila Yousefi, Gholamhossein Mehralian, Hamid Reza Rasekh and Hossein Tayeba

Pharmaceutical market value in Iran exceeded to more than US$4bn in 2013, indicating annually over 20 per cent growth. In the past decades, Iranian pharmaceutical industry was…

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Abstract

Purpose

Pharmaceutical market value in Iran exceeded to more than US$4bn in 2013, indicating annually over 20 per cent growth. In the past decades, Iranian pharmaceutical industry was supported by government policies, namely, generic substitution, import limitation and local production support; however, the local pharmaceutical manufacturer’s market share in value has been decreased gradually. This study aims to provide historical data on Iran pharmaceutical market to show the importance of new product development to attain greater market share and tries to motivate the pharmaceutical industry located in developing countries to develop more innovative medicines.

Design/methodology/approach

This is a descriptive cross-sectional study that investigates the Iranian pharmaceutical market by focusing on new products over a five-year period (2009-2014), and that was augmented by an expert panel to rank subjectively firms’ performance indicators to shed light on the importance of new product development to firms’ performance.

Findings

The expert panel results find out that new product development is one of the most important “result indicators” for Iranian pharmaceutical companies. Historically, in line with the experts’ opinion on the new product development, the Iranian pharmaceutical industry has shown its capability to develop new medicines by developing 3,095 new products (mostly new-to-firm) across about 100 firms. Despite this fact, the share of local manufacturers in new medicines’ market decreased from 52 per cent at the beginning of studied period to 24 per cent at the end, and the gap between the unit value of imported and domestically produced medicines has been significantly increased due to low-innovative medicines locally produced.

Research limitations/implications

This research was challenged with limitations such as lack of reliable published data on new medicines in the Iran pharmaceutical market.

Practical implications

This study highlights the fact that developing more innovative products in the generic pharmaceutical industry such as Iran can grant its market share.

Originality/value

This is an original study that shows the effect of innovative product development on market share through historical data.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 10 no. 4
Type: Research Article
ISSN: 1750-6123

Keywords

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Article
Publication date: 24 September 2019

Farman Afzal, Shao Yunfei, Mubasher Nazir and Saad Mahmood Bhatti

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to…

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Abstract

Purpose

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

Design/methodology/approach

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

Findings

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

Research limitations/implications

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

Practical implications

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

Originality/value

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

Details

International Journal of Managing Projects in Business, vol. 14 no. 2
Type: Research Article
ISSN: 1753-8378

Keywords

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Article
Publication date: 20 October 2023

Abdul Rehman Shaikh

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era…

162

Abstract

Purpose

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.

Design/methodology/approach

A review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.

Findings

This study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.

Practical implications

The results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.

Originality/value

This is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.

Details

Benchmarking: An International Journal, vol. 31 no. 10
Type: Research Article
ISSN: 1463-5771

Keywords

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