Assessing partnership alternatives in an IT network employing analytical methods

One of the main critical success factors for the companies is their ability to build and maintain an effective collaborative network. This is more critical in the IT industry where the development of sustainable competitive advantage requires an integration of various resources, platforms, and capabilities provided by various actors. Employing such a collaborative network will dramatically change the operations management and promote flexibility and agility. Despite its importance, there is a lack of an analytical tool on collaborative network building process. In this paper, we propose an optimization model employing AHP and multiobjective programming for collaborative network building process based on two interorganizational relationships’ theories, namely, (i) transaction cost theory and (ii) resource-based view, which are representative of short-term and long-term considerations. The five different methods were employed to solve the formulation and their performances were compared. The model is implemented in an IT company who was in process of developing a large-scale enterprise resource planning (ERP) system. The results show that the collaborative network formed through this selection process was more efficient in terms of cost, time, and development speed. The framework offers novel theoretical underpinning and analytical solutions and can be used as an effective tool in selecting network alternatives

A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed

Does CEO power moderate the link between labor productivity and financial performance: agency theory or stewardship theory

Purpose – This study investigates the moderating effect of CEO power on the relationship between labor productivity and financial performance in the Tehran Stock Exchange (TSE). Design/methodology/approach – In this study, the power of the CEO variable was measured using the power index method and its effect on the relationship between labor productivity and financial performance was tested using a multivariate regression. The study sample consisted of 1,040 observations and 130 firms listed on the TSE over an eight-year period between 2012 and 2019. Panel data and appropriate statistical techniques were applied to estimate models. In this study, Tobin’s Q and return on assets (ROA) are the two variables used to measure financial performance. Findings – The results of the hypotheses show that the link between labor productivity and financial performance based on Tobin’s Q and ROA strengthens with increasing CEO power. Thus, the stewardship theory is approved on the TSE. In addition, CEO power and labor productivity have a positive impact on firm performance. Research limitations/implications – To the best of the author’s knowledge, this is the first study to examine the moderating impact of CEO power on the relationship between labor productivity and firms' financial performance in emerging capital markets. Therefore, the results of this study can be used by investors, board of directors, policymakers and regulations. Practical implications – Taking into consideration the sanctions on Iran's economy during the study period and to increase the productivity and financial performance of the company, the results of this study can provide a practical guide for the board of directors to consider the characteristics of CEO power and how to choose it in the emerging capital market. Additionally, the study results show that investors should choose companies with strong CEO to invest in the Iranian capital market. Originality/value – The current study is the first study conducted in an emerging economy to examine the moderating impact of CEO power on the link between labor productivity and financial performance

Transforming Design Spaces Using Pareto-Laplace Filters

Optimization is a critical tool for addressing a broad range of human and technical problems. However, the paradox of advanced optimization techniques is that they have maximum utility for problems in which the relationship between the structure of the problem and the ultimate solution is the most obscure. The existence of solution with limited insight contrasts with techniques that have been developed for a broad range of engineering problems where integral transform techniques yield solutions and insight in tandem. Here, we present a ``Pareto-Laplace'' integral transform framework that can be applied to problems typically studied via optimization. We show that the framework admits related geometric, statistical, and physical representations that provide new forms of insight into relationships between objectives and outcomes. We argue that some known approaches are special cases of this framework, and point to a broad range of problems for further application.Comment: 28+19 pages, 3 figure

Big Data IoT-based Agile-Lean Logistic in Pharmaceutical Industries

Purpose: In today’s world, with the presence of huge volumes of data, although organizations have faced many problems, using big data analysis has been able to significantly improve their efficiency and integrate information in the supply chain through the topic of computing. Cloud and big data achieve coordination between components and improve communication. On the other hand, Internet of Things (IoT) technology tools are one of the most important sources of big data production, and understanding and correct use of this data and their timely analysis using big data analysis techniques and technologies based on artificial intelligence can be effective steps to improve supply chain processes. Also, the use of these technologies can play an important role in process agility and, as a result, supply chain resilience. Methodology: In this study, the dimensions and key components of the use of large data obtained from the Internet of Things (IoT) in an industry's supply chain are investigated as a case study. Finally, a model for implementing an agile and lean supply chain based on IoT data analysis to improve the supply chain performance of these industries during emergency drug distribution during critical conditions is presented. Findings: This study shows that these technologies can be used as a powerful enabler, especially in the distribution of fast-acting pharmaceutical products.                                                                         Originality/Value: In this paper a model for implementing an agile and lean supply chain based on IoT data analysis to improve the supply chain performance of these industries during emergency drug distribution during critical conditions is presented

Reduction in the balanced scorecard performance measurement systems in manufacturing organizations by PCA

In this paper, we compare PCA and ordinal logistic regression in ranking the manufacturing systems. In this regard we present an integrated framework for assessment and ranking of manufacturing systems based on management and organizational performance indicators. To achieve the objectives of this study, a comprehensive study was conducted to locate all economic and technical indicators which influence organizational performance. Sixty one indicators were identified and classified in .five categories, namely, (1) financial, (2) customer satisfaction, (3) process innovation, (4) production process and (5) organizational learning and growth. These indicators are related to organizational and managerial productivity and efficiency. One actual test problem and a random sample of 12 indicators were selected to show the applicability of the integrated approach. The results of PCA and OLR showed the weak and strong points of each sector in regard to the selected indicators. Furthermore, it identifies which indicators have the major impacts on the overall performance of industrial sectors. The modeling approach of this paper could be easily utilized for managerial and organizational ranking and analysis of other sectors. The results of such studies would help top managers to have better understanding and improve existing systems with respect to managerial and organizational performance.Keywords: Productivity and competitiveness; Multivariate statistics integrated assessment, BC

Synthesis and Antioxidant Properties of Two New Derivatives of Indeno-Benzofuran

Ninhydrin reacts with poly-phenols in different ratios to produce tetracyclic adducts. Here, pyrogallol was used as a polyphenol compound. In the company of acidic ionic liquid (AIL), there was a selective reaction between the ortho-site of polyphenol and the ninhydrin’s carbonyl group. Mono-adduct (1:1) 3 and bis-adduct (2:1) 4 were prepared as a solvent and a catalyst for the reaction of ninhydrin with pyrogallol in 1-(carboxymethyl)-3-methyl-1H-imidazolium chloride (mcmimCl). Purity of the products was approved by 1H NMR, 13C NMR, IR and Mass Spectroscopy. Moreover, the antioxidant activity of novel derivatives investigated in this paper by 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical assay and butylated hydroxytoluene (BHT) was considered to be standard. The results indicated that mono-adduct showed the strongest antioxidant activity (IC50 = 5.289µg/ml).&nbsp

AIoT-based Sustainable Smart Supply Chain Framework

Purpose: Supply chains in today's global environment operate in a market that is increasingly complex and dynamic in nature. In such an environment, a stable supply chain to respond to drastic changes in customer needs becomes inevitable. Based on these studies, it is obvious that organizations operating in the field of supply chain should accelerate their focus on sustainability and use technologies such as "Internet of Things" (IoT) and artificial intelligence to achieve the organization's goal of creating sustainable processes. Methodology: The presence of the Internet of Things, along with artificial intelligence technology, has created Artificial intelligence of things (AIoT) technology, which gives the big data from the Internet of Things great power. In this research, an attempt has been made to study and analyze the key dimensions, components and indicators of the AIoT-based sustainable supply chain. Also, a conceptual framework for Padidar intelligent supply chain based on these evolving technologies is presented, which can help to understand the elements of this intelligent supply chain in order to optimize. Findings: A study of the literature shows that investing in this technology to achieve sustainable benefits is inevitable. In addition, the use of this technology due to networking and the presence of the Internet requires appropriate security solutions for information technology, a workforce with the required set of skills, sharing information in an integrated environment with business partners. Originality/Value: The generalities of AIoT-based sustainable supply chain components in general, and things can be added to different industries and behaviors. Understanding the dimensions of this framework can always help to implement it effectively

An IoT-based sustainable supply chain framework and blockchain

The increasing expansion of the needs of human beings and societies has caused various aspects of human life and societies to face serious challenges and be considered. Supply chain organizations operate in a market in today's global environment that is increasingly complex and dynamic in nature. Stable supply chains are inevitable to meet drastic changes in customer needs. Research has shown that manufacturing companies need to accelerate the shift from focus to sustainability and use technologies such as the Internet of Things (IoT) and blockchain to achieve the organization's goal. In this regard, by expanding the capabilities of the blockchain under the four main areas (1) designing incentive and tokenization mechanisms to promote green consumer behavior; (2) increase visibility throughout the product life cycle; (3) increase system efficiency while reducing development and operating costs; And (4) strengthen the monitoring of sustainability and performance reporting in supply chain networks; it can be seen that the supply chain based on these transformational technologies can play a colorful role in creating stability and a green and efficient supply chain. In this study, the potential opportunities in the IoT to create a sustainable supply chain are discussed. Also, based on this study, a framework has been proposed to show the relationships and effects of the constituent elements of a stable supply chain system based on the Internet of Things and blockchain. The conceptual framework is designed with an emphasis on sustainable development, collaboration and management and can provide a good perspective for implementing a sustainable supply chain based on technolog

A framework for IoT and Blockchain Based on Marketing Systems with an Emphasis on Big Data Analysis

In today's world, huge amounts of information affect all aspects of our lives and play an important role in our decisions. The importance of big data in business, like other key processes in the organization, has not hidden from experts. Access to big data can play an important role in understanding audience behavior, planning advertising campaigns, deciding on a marketing mix such as changing a product and selecting its distribution channels, implementing e-marketing strategies, content production strategies, and many other micro and macro decisions. The Internet of Things as a transformative technology is one of the most important sources of big data production. The use of social networks and online platforms in marketing, allows companies to interact with consumers in a targeted manner and provide the required information as soon as possible. In addition to high volume, IoT data also has high accuracy and purity, based on performance. Despite all the positive features of IoT-based smart marketing and the presence of big data, the disclosure of private information is the main problem. Therefore, it is necessary to pay attention to methods, approaches and technologies that can help eliminate this complication. It seems that blockchain technology with features such as tracking, transparency and security enhancement, can help to eliminate this problem and improve the performance of the digital marketing industry. For this reason, this chapter of the book provides a conceptual framework for demonstrating the causal relationships of the elements that make up an intelligent marketing system based on these evolving technologies. Understanding this framework will help implement a smart and capable marketing system