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1 – 10 of 14Saeed Baghdadi, Abbas Khamseh and Seyed Hesamedin Madani
The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas…
Abstract
Purpose
The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas industry. Since commercialization models are mostly based on the implement of technology to produce and sell new products, this study focuses on developing a specific independent technology commercialization model.
Design/methodology/approach
The method of this research is qualitative based on the grounded theory. For this purpose, general variables with content analysis were extracted by reviewing documents (Literature review) and then for identifying special components, interviewing experts in the Iranian oil and gas industry. Participations were selected using snowball sampling for semistructured interviews.
Findings
The findings of this research were extracted based on grounded theory with data analysis in MAXQDA software. In this research, first, 210 open codes were identified based on qualitative content analysis of relevant documents and results of interviews with experts. Then the classification of open codes was done, and 46 subcategories (variables) were determined in the commercialization model. Finally, 46 subcategories were classified into 10 categories as axial codes in grounded theory as components of the commercialization model.
Research limitations/implications
The results of this research have led to the creation of new practical and theoretical implications. In this research, a new perspective of commercialization with the aim of transferring technology and obtaining its economic benefits for oil and gas industry companies was discussed. Also, based on the practical implications explained in this research, policymakers can use the suggested model to effectively implement independent technology commercialization to acquire economic benefits.
Originality/value
This study is purely original and the outcome of the research conducted by the authors. The research findings are the outcome of in-depth study on technology commercialization in the Iranian oil and gas industry.
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Chuleshwar Naik and Bijuna C. Mohan
The provision of fair and remunerative prices to farmers through government intervention is one of the key debates to address the farmers' distress in India. This article…
Abstract
Purpose
The provision of fair and remunerative prices to farmers through government intervention is one of the key debates to address the farmers' distress in India. This article identifies how different marketing channels are responsible for higher price realization over the officially announced minimum support price (MSP).
Design/methodology/approach
The study uses the NSSO-SAS, 2012–13 and NSSO-SAS, 2018–19 for Aggregate level data and Unit Level Data on the Situation Assessment Survey of Farmers' households. It uses logit regression to determine the factors responsible for better price realization.
Findings
Our major findings indicate that two factors importantly determine better price realization than MSP. Firstly, government agencies provide better prices for crops covered by MSP, such as paddy, wheat and cotton. However, the probability of receiving higher prices increases for some crops if the farmers belong to the upper land size classes and upper social category. Secondly, jowar, bajra, maize and ragi, other important crops that don't benefit from government agencies, may require higher levels of procurement at the state level.
Research limitations/implications
The present study only analyzes selected major crops. Distance is an important factor in choosing a marketing channel that is not incorporated due to unavailability in NSS Data.
Originality/value
The study is based on the latest original empirical evidence and sheds light on the variation in price realization in different agricultural marketing channels in India.
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Maria Angela Butturi, Francesco Lolli and Rita Gamberini
This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their…
Abstract
Purpose
This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.
Design/methodology/approach
A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.
Findings
A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.
Originality/value
Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.
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Shola Usharani, R. Gayathri, Uday Surya Deveswar Reddy Kovvuri, Maddukuri Nivas, Abdul Quadir Md, Kong Fah Tee and Arun Kumar Sivaraman
Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for…
Abstract
Purpose
Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.
Design/methodology/approach
In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.
Findings
A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.
Originality/value
The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.
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Nandun Madhusanka Hewa Welege, Wei Pan and Mohan Kumaraswamy
Despite carbon reduction commitments, many constraints hinder the delivery of low-carbon buildings (LCBs) in high-rise high-density cities. The collaborative commitment of…
Abstract
Purpose
Despite carbon reduction commitments, many constraints hinder the delivery of low-carbon buildings (LCBs) in high-rise high-density cities. The collaborative commitment of relevant stakeholders is vital to effectively address and mitigate these constraints. Hence, this study aims to comprehensively explore the required stakeholder collaboration attributes to address and mitigate the “common” constraints of delivering LCBs by focussing on several high-rise high-density cities.
Design/methodology/approach
A list of 21 “significant and common” constraints was identified through a systematic literature review followed by a questionnaire survey covering five economies (Hong Kong, Singapore, Australia, Qatar and the UAE). Nineteen influential stakeholders/stakeholder categories were identified through the literature, and their ability to influence the 21 constraints was mapped and identified through a two-round Delphi survey of 15 experienced professionals. The Delphi survey findings were analysed through social network analysis (SNA) methods to assess the stakeholder engagement and collaboration attributes.
Findings
The SNA results revealed the ability of stakeholders to influence the constraints, required collaborative stakeholder networks to address the constraints, significance of stakeholders according to the SNA centrality measures, core and periphery stakeholders and individual co-affiliation networks of core stakeholders.
Originality/value
While achieving the planned primary target of exploring stakeholder collaboration and their significance through SNA, this study also presents a useful sequential methodological approach for future researchers to conduct similar studies in different contexts. The findings also provide a foundation for accelerating the delivery of LCBs by strengthening stakeholder collaboration.
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Ziaul Haque Munim, Dhanavanth Reddy Maditati, Sebastian Kummer and Hans-Joachim Schramm
This study aims to explore the gaps concerning the organizational operant resources (OORs) of logistics service providers (LSPs) expected in outsourcing relationships. The study…
Abstract
Purpose
This study aims to explore the gaps concerning the organizational operant resources (OORs) of logistics service providers (LSPs) expected in outsourcing relationships. The study considers the views of both manufacturing firms (M-firms) and LSPs in India and DACH region (Germany, Austria and Switzerland) seeking gaps within and across regions.
Design/methodology/approach
This research employed a survey targeting executives from large M-firms and LSPs in both India and DACH. The perceptions about the importance and improvement expectations of 17 OORs are analyzed. A modified version of importance-improvement analysis (A-B), a novel comparative A-B analysis (CABA) method, has been proposed to identify the importance and improvement gaps in OORs between M-firms and LSPs within and across India and the DACH region.
Findings
There are more gaps between M-firms and LSPs in India compared to DACH. Cross-country comparisons reveal that LSPs in India and DACH have similar perceptions concerning the OORs, but M-firms in India have significantly higher improvement expectations than those in DACH.
Research limitations/implications
This study proposes an analytical approach that enables managers to identify improvement areas and better align with their outsourcing relationship partners. It also highlights aspects that need to be considered while entering emerging markets such as India.
Originality/value
The analysis approach using CABA is novel. Also, among the cross-country studies, this is the first to compare outsourcing relationships in India with the DACH region while involving both users' and service providers' perspectives.
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The present study aims to comprehensively examine the impact of the Union Bank of Switzerland (UBS) takeover of Credit Suisse on the banking and financial services sector in the…
Abstract
Purpose
The present study aims to comprehensively examine the impact of the Union Bank of Switzerland (UBS) takeover of Credit Suisse on the banking and financial services sector in the Indian stock market. To fully comprehend the impact of the event, the study separately investigates the response of private sector banks, public sector banks, overall banking companies and financial services companies to the takeover of the second-largest financial institution in Switzerland.
Design/methodology/approach
The study employs event study methodology, using the market model, to analyze the event's impact on Indian banking and financial services sector stocks. The data consists of daily closing prices of companies included in the Nifty Private Bank Index, Nifty PSU Bank Index, Nifty Bank Index and Nifty Financial Services Index from the National Stock Exchange (NSE). Furthermore, cross-sectional regression analysis has been conducted to explore the factors that drive abnormal returns.
Findings
The empirical findings of the study suggest the event had a heterogeneous impact on the stock prices of Indian banks and financial services companies. While public sector banks experienced a significant negative impact on select days within the event window, the overall Indian banking sector and financial services companies also witnessed notable declines. In contrast, Indian private sector banks were relatively resilient, exhibiting minimal effects. However, the cumulative effect is found to be insignificant for all four categories across different event windows. The study also observed that the cumulative abnormal returns (CARs) were significantly influenced by certain variables during different event windows.
Originality/value
To the best of the authors' knowledge, the present study is the earliest attempt that investigates the impact of the UBS takeover of Credit Suisse on the Indian banking and financial services sector using event study methodology and cross-sectional regression model.
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Md Tariqul Islam, Shrabani Saha and Mahfuzur Rahman
The empirical study aims to examine the impact of board diversity with respect to gender and nationality on firm performance in an emerging economy. This research further splits…
Abstract
Purpose
The empirical study aims to examine the impact of board diversity with respect to gender and nationality on firm performance in an emerging economy. This research further splits the sample into family and non-family domains and investigates the diversity–performance nexus in isolation.
Design/methodology/approach
The sample consists of 183 listed companies in Bangladesh over the period 2007 to 2017. This study employed the generalised method of moments (GMM) technique to address the possible endogeneity issue in the governance–performance connection. To underscore the strength of diversity, three distinctive assessment measures were used: percentage representation of females and foreign directors, the Blau index and the Shannon index.
Findings
The results for the full sample models reveal that board heterogeneity regarding both female and foreign directors positively and significantly influences firm performance as measured by return on assets (ROA). Further to this, female directors in family-owned businesses have a positive association with profitability, whereas foreign nationals demonstrate a significant positive association with performance in non-family firms. Additionally, at least three women directors are needed to make a positive difference in profitability; however, a sole director with foreign nationality is capable of demonstrating a similar impact on performance.
Practical implications
The findings are significant for policymakers and organisations that advocate diversity on corporate boards of directors, and the minimum number of diverse board members needs to be considered depending on the identity to bring about a significant change in organisational outcome. Therefore, the findings of this study may be applied to other emerging economies with similar institutional characteristics.
Originality/value
This study reinforces the existing stock of knowledge on the impact of board diversity on the profitability of firms, especially in the context of an emerging economy – Bangladesh. Irrespective of the given backdrop, this study finds that both gender and nationality diversity in the case of Bangladesh is found to have a positive and significant effect on financial performance with respect to all the diversity metrics, i.e. the proportionate number of female and foreign directors on the boards, the Blau index and the Shannon index.
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Xiangju Meng, Zhenfang Hu and Dan Jia
This paper aims to explore the impact of a digital growth mindset on the academic performance of business students in China as well as the role of gender in this relationship. The…
Abstract
Purpose
This paper aims to explore the impact of a digital growth mindset on the academic performance of business students in China as well as the role of gender in this relationship. The study provides feasible ways to foster such a mindset to ensure quality in business education.
Design/methodology/approach
The paper employs a survey to examine the associations among digital growth mindset, gender and the academic performance of business students in China within the context of online learning. The authors collected data from 533 students who were enrolled in two online business courses at a Chinese university. The data were paired and analyzed through regression analysis.
Findings
The empirical results show that digital growth mindset has a positive influence on the academic performance of business students in China. The relationship is stronger for male business students than for their female counterparts.
Originality/value
This study is one of the first to examine the concept of digital growth mindset and its significance in Chinese business education. Through the analysis of paired data on digital growth mindset and academic performance, this study makes theoretical contributions to the literature on growth mindset, gender differences and academic success. Additionally, it has practical implications for quality assurance in business education in developing countries by offering feasible approaches to cultivate a growth mindset among students.
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Ibrahim A. Amar, Aeshah Alzarouq, Wajdan Mohammed, Mengfei Zhang and Noarhan Matroed
This study aims to explore the possibility of using magnetic biochar composite (MBCC) derived from Heglig tree bark (HTB) powder (agricultural solid waste) and cobalt ferrite (CoFe…
Abstract
Purpose
This study aims to explore the possibility of using magnetic biochar composite (MBCC) derived from Heglig tree bark (HTB) powder (agricultural solid waste) and cobalt ferrite (CoFe2O4, CFO) for oil spill removal from seawater surface.
Design/methodology/approach
One-pot co-precipitation route was used to synthesize MBCC. The prepared materials were characterized by X-ray diffraction, scanning electron microscopy-energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy. The densities of the prepared materials were also estimated. Crude, diesel engine and gasoline engine oils were used as seawater pollutant models. The gravimetric oil removal (GOR) method was used for removing oil spills from seawater using MBCC as a sorbent material.
Findings
The obtained results revealed that the prepared materials (CFO and MBCC) were able to remove the crude oil and its derivatives from the seawater surface. Besides, when the absorbent amount was 0.01 g, the highest GOR values for crude oil (31.96 ± 1.02 g/g) and diesel engine oil (14.83 ± 0.83 g/g) were obtained using MBCC as an absorbent. For gasoline engine oil, the highest GOR (27.84 ± 0.46 g/g) was attained when CFO was used as an absorbent.
Originality/value
Oil spill removal using MBCC derived from cobalt ferrite and HTB. Using tree bark as biomass (eco-friendly, readily available and low-cost) for magnetic biochar preparation also is a promising method for minimizing agricultural solid wastes (e.g. HTB) and obtaining value-added-products.
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