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

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

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

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

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

Modeling national innovation system enabled by knowledge management

The main objective of this paper is to explore the model of how knowledge management functions enables national innovation system. To achieve the objectives of the study, a conceptual framework is proposed and described, then the systemic analysis is undertaken. Path coefficient and t-value are also used to measure the relationships among chosen variables. A great number of sources are used to collect data, including questionnaires, interviews, observations, and literature review. The achievements of the study demonstrate 10 distinctive national innovation system performance dimensions and the relationship with knowledge management functions. The first layer includes explicit knowledge, while the second layer deals with tacit knowledge. Both of two layers link to a complete knowledge management functions and processes: explicit knowledge building, explicit knowledge gathering, explicit knowledge distributing, explicit knowledge reusing, tacit knowledge capturing, tacit knowledge sharing tacit knowledge disseminating, tacit knowledge innovating; whereas the third layer includes NIS enablers items or performance dimension of national innovation system: quality, effectiveness, quantity, codification, structure, efficiency, internalization, expertise, effectiveness

Non-thermal plasma radiation-induced changes in antibiotic susceptibility and protein profile of Staphylococcus aureus

Background and Objectives: Plasma radiation is a widely used technique for sterilization or decontamination in various industries, as well as in some healthcare settings such as dentistry. The primary aim of this study was to assess the potential of plasma radiation to create a new population of Staphylococcus aureus cells with distinct characteristics that could lead to novel healthcare challenges. Materials and Methods: A homemade non-thermal plasma apparatus was applied and the effects of plasma treatment on S. aureus ATCC25923 was assessed. Plasma radiation was applied under controlled conditions to ensure that some bacterial cells remained viable. The treatment was repeated 10 times, with each round followed by a recovery phase to collect any surviving bacterial cells. To assess the potential changes in the bacterial population, we examined the antibiotic susceptibility pattern, micro-structural characteristics using scanning electron microscopy (SEM), and total protein profile using the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) technique. Results: The experimental results revealed slight variations in the antibiotic susceptibility patterns of certain cell wall agents (imipenem, cephalothin, and cefepime), as well as in the MALDI-TOF spectra. However, no changes were observed in the SEM images. Conclusion: The insufficient application of non-thermal plasma in bacterial decontamination may lead to physiological changes that could enrich or select certain subpopulations of S. aureus

Observation and Measurement of Negative Differential Resistance on PtSi Schottky Junctions on Porous Silicon

Nanosize porous Si is made by two step controlled etching of Si. The first etching step is carried on the Si surface and the second is performed after deposition of 75 Å of platinum on the formed surface. A platinum silicide structure with a size of less than 25 nm is formed on the porous Si surface, as measured with an Atomic Forced Microscope (AFM). Differential resistance curve as a function of voltage in 77 K and 100 K shows a negative differential resistance and indicates the effect of quantum tunneling. In general form, the ratio of maximum to minimum tunneling current (PVR) and the number of peaks in I–V curves reduces by increasing the temperature. However, due to accumulation of carriers behind the potential barrier and superposition of several peaks, it is observed that the PVR increases at 100 K and the maximum PVR at 100 K is 189.6