• Can environmental investments benefit environmental performance? the moderating roles of institutional environment and foreign direct investment

      Li, Ruiqian; Ramanathan, Ramakrishnan (John Wiley & Sons Ltd, 2020-06-18)
      Contribution of environmental investments (EI) to environmental performance (EP) is a lively topic for environmental researchers across the world. In spite of huge amount of research, there is still lack of clarity on the moderating factors that affect the role played by EI. In this study, we distinguish EI into pollution control investments (PCI) and pollution prevention investments (PPI). We further investigate whether institutional environment and foreign direct investment (FDI) can play their moderating effects both on the relationship between EI and EP and on the relationships between different types of investments and EP or not. The results indicate that EI has a positive effect on EP. More specifically, PPI plays a stronger positive role in EP, but PCI does not have a significant effect on EP. In addition, both institutional environment and FDI can strengthen the positive impact of EI on EP. The increase of EI in regions with better institutional environment or high FDI can lead to greater improvement in EP. These moderating effects of institutional environment and FDI are also confirmed on the link between PPI and EP. In summary, our results reinforce the existing views that EI, and specifically PPI, can improve EP, but further contribute to the understanding of the positive moderating roles played by the institutional environment and FDI on the link between EI and EP.
    • Opening the black box: the impacts of environmental regulations on technological innovation

      Li, Muyao; Zhang, Jinsong; Ramanathan, Ramakrishnan; Li, Ruiqian; ; Harbin University of Commerce; University of Bedfordshire; Heilongjiang University (MDPI, 2020-06-16)
      Whether environmental regulations (ERs) can stimulate technological innovation (TI) is the key for realizing the win-win strategy between economic development and environmental protection. This study seeks to analyze the impacts of ERs on TI. Though previous literature has highlighted that the black box of TI can be decomposed into technology investment and technology transformation, further empirical studies on such a decomposition has largely been ignored. Moreover, a detailed discussion of the links between ER and the decomposed components of TI has not been conducted in developing countries such as China. Our study attempts to address these research gaps by (i) decomposing TI using a novel DEA procedure and to further analyze the impacts of ERs on the decomposed components of TI, and (ii) apply this novel methodology to Chinese context. Accordingly, this study is conducted in two stages. First, a novel application of the slack-based Network DEA model is developed to uncover the black box of TI using Chinese data; to estimate the overall efficiency of technological innovation (TIE) and decompose it into the efficiency of technology investment (TVE) and the efficiency of technology transformation (TTE). Second, a random effect Tobit model is applied to (i) investigate both the linear and non-linear impacts of ERs on TIE in all sectors, and (ii) examine whether the impacts of ERs on TVE and TTE in different sub-processes are heterogeneous or not. Our results have brought out the benefits of decomposing TI; while technology transformation in China closely follows the trend of TI, the trend of technology investment is somewhat different. The estimation results further indicate that the impacts of ERs on TIE are non-linear. Besides, ERs have heterogeneous impacts on the decomposed components of TI. The impacts of ERs on TVE are non-linear, whereas the impacts of ERs on TTE become insignificant.
    • Modelling world natural gas production

      Wang, Jianliang; Bentley, Yongmei; ; China University of Petroleum; University of Bedfordshire (Elsevier, 2020-05-23)
      As the cleanest fossil fuel in terms of carbon dioxide (CO2) emissions, natural gas demand is expected to increase rapidly in future due to its important role in the transition of the world energy system. In this case, understanding potential limits to future production of the world’s natural gas resources becomes increasingly important. This paper uses a modified multi-cycle generalized Weng model to forecast the long-term production of natural gas by region, and also globally. Both conventional and unconventional gas production are considered. Our results show that world natural gas production is likely to peak in the range 3.7 to 6.1 trillion cubic meters per year (tcm/y) between 2019 and 2060 depending on assumptions made on the size of the global ultimately recoverable resource (URR) of natural gas. A comparison of this paper’s forecasts with those from the scientific literature and from major energy institutes shows that the projection in this paper’s ‘high scenario’ can be seen as a likely upper-bound on future global natural gas production. To turn this upper-bound projection into reality, great efforts will be needed from the gas industry to discover more conventional and unconventional gas resources, and to make these recoverable.
    • Automatic recognition methods of fish feeding behavior in aquaculture: a review

      Li, Daoliang; Wang, Zhenhu; Wu, Suyuan; Miao, Zheng; Du, Ling; Duan, Yanqing; ; China Agricultural University; Renmin University of China; University of Bedfordshire (Elsevier, 2020-05-23)
      Feeding is a major factor that determines the production costs and water quality of aquaculture. Analysis of fish feeding behavior forms an important part of the feeding optimization. Fish feeding has generally been performed with automatic feeding machines which can lead to excessive or insufficient feeding. Recognition of fish feeding behavior can provide valuable input for optimizing feeding quantity. Due to the complexity of the environment and the uncertainty of fish behavior, the correlation and accuracy of behavior recognition are generally low. The accurate identification of fish feeding behavior till faces substantial challenges. This paper reviews the technical methods that have been used to identify fish feeding behavior in aquaculture over the past 30 years. The advantages and disadvantages of each method under different experimental conditions and applications are analyzed. Many methods are effective at evaluating and quantifying fish feeding intensity, but the recognition accuracy still needs further improvement. It is proposed by this paper that technologies such as data fusion and deep learning has great potential for improving the recognition of fish feeding behavior.
    • Recent advances in sensor fault diagnosis: a review

      Li, Daoliang; Wang, Ying; Wang, Jinxing; Wang, Cong; Duan, Yanqing; China Agricultural University; Shandong Agricultural University; University of Bedfordshire (Elsevier, 2020-05-11)
      As an essential component of data acquisition systems, sensors have been widely used, especially in industrial and agricultural sectors. However, sensors are also prone to faults due to their harsh working environment. Therefore, the early identification of sensor faults is critical for making corrective actions to mitigate the impact. This paper provides a comprehensive review on the contemporary fault diagnosis techniques and helps researchers and practitioners to understand the current state of the art development in this emerging field. The paper introduces the common fault types and causes in sensors, and different types’ methods for fault diagnosis used in industry and agriculture sectors. It discusses the advantages and disadvantages of these methods, highlights the current challenges, and offers recommendations for future research directions.
    • Factors motivating Indian manufacturing SME employers’ to adopt GSCM practices

      Khillon, M.; Bentley, Yongmei (Springer, 2020-05-06)
      The growth of manufacturing SMEs is vital, as their contribution towards the national economy is significant. In this era of globalisation, SMEs are compelled to ensure sustainable profitability through cost saving, while being environmentally conscious at the same time. It has been reported in the past empirical studies, that adoption of green supply chain management (GSCM) practices by SMEs could enable such enterprises to improve their performance and succeed in their operations. Hence, to gain and maintain competitive advantage and succeed, SMEs need to change their practices and adapt their strategies to the dynamic environment of today. The factors motivating adoption of GSCM among Indian SMEs have not been thoroughly explored in the past studies. This sets the motivation for the present research. Thus, the purpose of this paper is to explore the factors motivating Indian manufacturing SME employers in adopting GSCM practices in their firms and to develop a GSCM framework based on the literature review and the empirical findings of this study.
    • Best practices in the cost engineering of through-life engineering services in Life Cycle Costing (LCC) and Design To Cost (DTC)

      Baguley, Paul (Springer, 2020-04-30)
      This chapter defines a number of Cost Engineering challenges from industry and their potential best practice solutions as industry case studies and industry practices surveys completed during the previous 5 years. In particular Life Cycle Costing in the context of upgrade and revamp in the process industry and also an example of design for full life cycle target cost for the manufacturing industry. Life Cycle Costing of complex long life cycle facilities is exemplified by identification and development of a life cycle costing of oil refineries through a survey of 15 companies and full life cycle experts and a review of the literature. Life cycle costing practices and a standardised life cycle cost breakdown structure are identified. Design to full life cycle target cost practices have been identified in the development of a full life cycle cost estimating tool for marine radar systems. In particular a survey of 17 companies and a case study with a marine radar systems company has identified specific practices useful in developing products to full life cycle target cost. In planning for future Through Life Engineering Services it is proposed that the collection of cost data and the understanding of Cost Engineering practices is a potential competitive advantage.
    • Integration of cost-risk assessment of denial of service within an intelligent maintenance system

      Carlander, L.; Kirkwood, Leigh; Shehab, Essam; Baguley, Paul; Durazo-Cardenas, Isidro; Cranfield University (Elsevier, 2020-04-29)
      As organisations become richer in data the function of asset management will have to increasingly use intelligent systems to control condition monitoring systems and organise maintenance. In the future the UK rail industry is anticipating having to optimize capacity by running trains closer to each other. In this situation maintenance becomes extremely problematic as within such a high-performance network a relatively minor fault will impact more trains and passengers; such denial of service causes reputational damage for the industry and causes fines to be levied against the infrastructure owner, Network Rail.     Intelligent systems used to control condition monitoring systems will need to optimize for several factors; optimization for minimizing denial of service will be one such factor. With schedules anticipated to be increasingly complicated detailed estimation methods will be extremely difficult to implement. Cost prediction of maintenance activities tend to be expert driven and require extensive details, making automation of such an activity difficult. Therefore a stochastic process will be needed to approach the problem of predicting the denial of service arising from any required maintenance. Good uncertainty modelling will help to increase the confidence of estimates.      This paper seeks to detail the challenges that the UK Railway industry face with regards to cost modelling of maintenance activities and outline an example of a suitable cost model for quantifying cost uncertainty. The proposed uncertainty quantification is based on historical cost data and interpretation of its statistical distributions. These estimates are then integrated in a cost model to obtain accurate uncertainty measurements of outputs through Monte-Carlo simulation methods. An additional criteria of the model was that it be suitable for integration into an existing prototype integrated intelligent maintenance system. It is anticipated that applying an integrated maintenance management system will apply significant downward pressure on maintenance budgets and reduce denial of service. Accurate cost estimation is therefore of great importance if anticipated cost efficiencies are to be achieved. While the rail industry has been the focus of this work, other industries have been considered and it is anticipated that the approach will be applicable to many other organisations across several asset management intensive industries.   
    • Applying blockchain technology to improve agri-food traceability: a review of development methods, benefits and challenges

      Feng, Huanhuan; Wang, Xiang; Duan, Yanqing; Zhang, Jian; Zhang, Xiaoshuan; University of Bedfordshire; China Agricultural University; Beijing Information Science and Technology University (Elsevier, 2020-03-11)
      Traceability plays a vital role in food quality and safety management. Traditional Internet of Things (IoT) traceability systems provide the feasible solutions for the quality monitoring and traceability of food supply chains. However, most of the IoT solutions rely on the centralized server-client paradigm that makes it difficult for consumers to acquire all transaction information and to track the origins of products. Blockchain is a cutting-edge technology that has great potential for improving traceability performance by providing security and full transparency. However, the benefits, challenges and development methods of blockchain-based food traceability systems are not yet fully explored in the current literature. Therefore, the main aim of this paper is to review the blockchain technology characteristics and functionalities, identify blockchain-based solutions for addressing food traceability concerns, highlight the benefits and challenges of blockchain-based traceability systems implementation, and help researchers and practitioners to apply blockchain technology based food traceability systems by proposing an architecture design framework and suitability application analysis flowchart of blockchain based food traceability systems. The results of this study contribute to better understanding and knowledge on how to improve the food traceability by developing and implementing blockchain-based traceability systems. The paper provides valuable information for researchers and practitioners on the use of blockchain-based food traceability management and has a positive effect on the improvement of food sustainability.
    • Transport analytics in action: a cloud-based decision support system for efficient city bus transportation

      Mathirajan, Muthu; Devadas, Rajesh; Ramanathan, Ramakrishnan; Indian Institute of Science; University of Bedfordshire (IOS Press / Taylor & Francis, 2020-03-05)
      Optimising city bus transport operations helps conserve fuel by providing the urban transport service as efficiently as possible. This study develops a Cloud-based Decision Support System (C-DSS) for transport analytics. The C-DSS is based on an intelligent model on location of depots for opening new depots and/or closing a few existing depots and allocation of city-buses to depots. The C-DSS is built on the Cloud Computing architecture with three layers and includes an efficient and simple greedy heuristic algorithm. Using modern information and communications technology tools, the proposed C-DSS minimizes the cost of city bus transport operations and in turn to reduce fuel consumption and CO2 emissions in urban passenger transport. The proposed C-DSS is demonstrated for its workability and evaluated for its performance on 25 large scale pseudo data generated based on the observation from Bangalore Metropolitan Transport Corporation (BMTC) in India.
    • The availability of critical minerals for China’s renewable energy development: an analysis of physical supply

      Wang, Jianliang; Yang, Lifang; Bentley, Yongmei; Lin, Jingli (Springer, 2020-01-13)
      In the context of depletion of fossil energy and environmental impacts of its use, society has begun to develop vigorously renewable energy (RE). As a result, concerns about the availability of critical minerals used in RE systems have been raised. This paper uses a generalized Weng model to analyze the long-term production of critical minerals for China’s RE development. In our pessimistic case, the results show that the production of most of the minerals investigated for China will peak before 2030, with a relatively high decline rate thereafter. This is an unsustainable situation for China’s RE development unless large and growing quantities of these minerals can be imported. In our optimistic case, although this delays the peak date only slightly, it significantly increases the maximum production rate and lowers the subsequent decline rate. The impacts of many other factors on production, and the implications of China’s domestic minerals production on world’s minerals supply chain, are also analyzed. We conclude that both China and the world should pay close attention to the potential supply risks to critical minerals. Possible measures in response are suggested for both China and the world.
    • Designing an organization for innovation in emerging economies: the mediating role of readiness for innovation

      Arshi, Tahseen Anwer; Burns, Paul; Majan University College; University of Bedfordshire (Vilnius University Press, 2019-12-31)
      The study proposes an organizational design framework that impacts innovation in corporate firms. In an emerging economy like Oman, innovation helps to reduce the dependence on oil revenues and enhance its international competitiveness. However, the corporate organizations in emerging economies are unable to innovate effectively because they are not designed for innovation. Further, scarcity of resources undermines their readiness for innovation. This study empirically validates measures of an entrepreneurial organizational design framework in Omani corporate sector. In order to explain how a corporate organizational design promotes innovation and clarify the missing links between corporate entrepreneurial activity and innovation, the mediating role of readiness for innovation (RFI) is tested. Using a quantitative research approach, data is collected from 401 corporate firms in Oman and analysed using structural equation modelling. The findings support the proposition that entrepreneurial organizational design promotes both radical and incremental innovation degree and frequency, while RFI partially mediates the relationship between entrepreneurial inputs and innovation outputs. The study contributes to the understanding of innovation in emerging economies as it explains that RFI helps firms to enhance its innovation potential by optimizing its resources, capabilities and processes for innovation. These measures are essential for organizations, particularly in emerging economies focused on low cost innovation. The findings of the study will inform managerial decision-making in terms of designing organizations for innovation and implementation of measures related to readiness for innovation. PDF
    • Application of graphene-based materials for detection of nitrate and nitrite in water—a review

      Li, Daoliang; Wang, Tan; Li, Zhen; Xu, Xianbao; Wang, Cong; Duan, Yanqing; China Agricultural University; University of Bedfordshire (MDPI AG, 2019-12-20)
      Nitrite and nitrate are widely found in various water environments but the potential toxicity of nitrite and nitrate poses a great threat to human health. Recently, many methods have been developed to detect nitrate and nitrite in water. One of them is to use graphene-based materials. Graphene is a two-dimensional carbon nano-material with sp2 hybrid orbital, which has a large surface area and excellent conductivity and electron transfer ability. It is widely used for modifying electrodes for electrochemical sensors. Graphene based electrochemical sensors have the advantages of being low cost, effective and efficient for nitrite and nitrate detection. This paper reviews the application of graphene-based nanomaterials for electrochemical detection of nitrate and nitrite in water. The properties and advantages of the electrodes were modified by graphene, graphene oxide and reduced graphene oxide nanocomposite in the development of nitrite sensors are discussed in detail. Based on the review, the paper summarizes the working conditions and performance of different sensors, including working potential, pH, detection range, detection limit, sensitivity, reproducibility, repeatability and long-term stability. Furthermore, the challenges and suggestions for future research on the application of graphene-based nanocomposite electrochemical sensors for nitrite detection are also highlighted.
    • Data of the impact of aligning business, IT, and marketing strategies on firm performance

      Al-Surmi, Abdulrahman Mohamed; Cao, Guangming; Duan, Yanqing; University of Bedfordshire (Elsevier, 2019-10-15)
      The data presented in this article are related to the research article entitled “The Impact of Aligning Business, IT, and Marketing Strategies on Firm Performance” [https://www.sciencedirect.com/science/article/pii/S0019850118304449]. In order to succeed in today's competitive business environment, a firm should have a clear business strategy that is supported by other organizational strategies. While prior studies argue that strategic alignment enhances firm performance, either strategic alignment including multiple factors or strategic orientation of firms has received little attention. This study, drawing on contingency theory and configuration theory, investigates the performance impact of triadic strategic alignment among business, IT, and marketing strategies while simultaneously considers strategic orientation of firms. A research model is tested through SEM and MANOVA using data collected in a questionnaire survey of 242 Yemen managers. The findings indicate that (1) triadic strategic alignment has a positive impact on firm performance and (2) there is an ideal triadic strategic alignment for prospectors and defenders. This research contributes to strategic alignment literature and managers' understanding of how to align business, IT and marketing strategies to improve firm performance.
    • Overcoming the novelty effect in online gamified learning systems: an empirical evaluation of learner engagement and performance

      Tsay, Crystal Han-Huei; Kofinas, Alexander K.; Trivedi, S.K.; Yang, Yang (Wiley, 2019-10-11)
      Learners in the Higher Education context who engage with computer-based gamified learning systems often experience the novelty effect: a pattern of high activity during the gamified system's introduction followed by a drop in activity a few weeks later, once its novelty has worn off. We applied a two-tiered motivational, online gamified learning system over two years, and used three-years' worth of longitudinal data to assess students' engagement and performance in that period. Quantitative results suggest that students engaged and performed better in the gamified condition vis-à-vis the non-gamified. Likewise, they sustained engagement better in the second year compared to the first year of the gamified condition. Our qualitative data suggests that students in the second year of the gamified delivery exhibited sustained engagement, bypassing the novelty effect. Thus, we suggest that sustained engagement with computer-based gamified learning systems beyond the novelty effect relies in making the engagement meaningful and useful for the students.
    • The role of government and the international competitiveness of SMEs Evidence from Ghanaian non-traditional exports

      Appiah, Kenneth; Osei, Collins; Selassie, Habte; Osabutey, Ellis (Emerald, 2019-10-07)
      Purpose The nature of international markets and the challenges with respect to the competitiveness of small- and medium-sized enterprises (SMEs) makes it imperative to examine government support. This study aims to assess the role and effectiveness of government and the export promotion agencies in supporting exports by non-traditional horticultural SMEs in Ghana. Design/methodology/approach The study used a qualitative research design, which involved semi-structured interviews with senior managers of six export facilitating institutions to gain an understanding of the services offered to SMEs with respect to exports of non-traditional horticultural products. Findings The findings reveal inadequate cost-efficient sources of non-traditional horticultural export financing for SMEs. This is a hindrance to the international competitiveness of exporting SMEs in developing countries such as Ghana. In addition, effective and coordinated support from export promotion agencies was found to be critical. Originality/value The study highlights the importance of government's role in policymaking and implementation of export-led programmes for horticultural exporting firms in Ghana. Despite their strategic importance, this area of research has not attracted the attention of researchers, with little or no information on the horticultural international competitiveness of non-traditional horticultural products.
    • Nonintrusive methods for biomass estimation in aquaculture with emphasis on fish: a review

      Li, Daoliang; Hao, Yinfeng; Duan, Yanqing (Wiley, 2019-09-30)
      Fish biomass estimation is one of the most common and important practices in aquaculture. The regular acquisition of fish biomass information has been identified as an urgent need for managers to optimize daily feeding, control stocking densities and ultimately determine the optimal time for harvesting. However, it is difficult to estimate fish biomass without human intervention because fishes are sensitive and move freely in an environment where visibility, lighting and stability are uncontrollable. Until now, fish biomass estimation has been mostly based on manual sampling, which is usually invasive, time‐consuming and laborious. Therefore, it is imperative and highly desirable to develop a noninvasive, rapid and cost‐effective means. Machine vision, acoustics, environmental DNA and resistivity counter provide the possibility of developing nonintrusive, faster and cheaper methods for in situ estimation of fish biomass. This article summarizes the development of these nonintrusive methods for fish biomass estimation over the past three decades and presents their basic concepts and principles. The strengths and weaknesses of each method are analysed and future research directions are also presented. Studies show that the applications of information technology such as advanced sensors and communication technologies have great significance to accelerate the development of new means and techniques for more effective biomass estimation. However, the accuracy and intelligence still need to be improved to meet intensive aquaculture requirements. Through close cooperation between fisheries experts and engineers, the precision and the level of intelligence for fish biomass estimation will be further improved based on the above methods.
    • Artificial Intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

      Dwivedi, Yogesh K.; Hughesa, Laurie; Ismagilova, Elvira; Aarts, Gert; Coombs, Crispin; Crick, Tom; Duan, Yanqing; Dwivedi, Rohita; Edwards, John; Eirug, Aled; et al. (Elsevier, 2019-08-27)
      As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial,intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.
    • Green supply chain management – practices and trends in developing countries

      Bentley, Yongmei; Dhillon, Manpreet Kaur (Springer, 2019-07-29)
      Purpose - The emergent issue of green supply chain management (GSCM) has been rapidly evolving, matched by the growth in the number of academic publications in this field. GSCM that incorporates environmental thinking into the supply chain management activities has gained popularity across the world, but mainly in the developed countries though the trend is noticeable in developing countries as well. The purpose of this research is to explore the existing studies in the field of GSCM in developing countries via a comprehensive systematic literature review (SLR) and compare the findings to those of the developed countries. Thus, this research aims to present the GSCM research from a comprehensive point of view and analyse the trend of growth in the last two and a half decades using the SLR method. Design/Methodology/Approach – This study uses the SLR approach to explore the present status of GSCM research in developing countries. Journal articles pertaining to GSCM in developed countries has also been studied for the purpose of comparing the results with the developing countries. For this review, Scopus and web of science database have been searched for papers published between 1990 and 2018 using the keywords ‘green supply chain management’ and ‘GSCM’. Articles identified were further reviewed and categorized under different attributes namely year, journal, geographical regions, research design, research methodology, and finally research issues. The classifications enabled the identification of crucial gaps in the literature for further research. Expected Outcomes – One of the main findings is that the research in GSCM has been dominated by quantitative study with mathematical modeling and surveys as the most commonly used methods to study GSCM issues. The full chapter will reveal the present status of GSCM research in developing countries in comparison with that in the developed countries. Thus, the results should improve the understanding of GSCM research in both developed and developing countries and highlight the opportunities that still need further investigation. Originality/Value - This study is original. The SLR method graphically illustrates the evolution of publications in developing countries over last quarter of a century in comparison to that with those in developed countries. This research has identified the gaps and directions that should be useful to guide researchers and practitioners in this area.
    • Investigating the practices of project governance in public sector infrastructure program in Pakistan

      Khan, Asadullah; Waris, Muhammad; Ismail, Ishak; Sajid, Mirza Rizwan; Ali, Zaigham; Ullah, Mahfooz; Hussain, Ammar; Universiti Malaysia Pahang; University of Gujrat; Karakoram International University; et al. (Hindawi Limited, 2019-06-04)
      The governance of public sector infrastructure projects became an important area of interest in the literature on project management. Today, it is a focal point for policymakers to ensure successful appraisal and implementation of government-sponsored programs. This paper aims to investigate the current practices of project governance (PG) for steering the public sector infrastructure program in Pakistan. An empirical investigation was carried out among professionals of public sector organizations involved in different infrastructure development projects. Latent construct of PG was validated through second-order confirmatory factor analysis (CFA) and quantified the three dimensions of PG, i.e., portfolio direction (PD), sponsorship, effectiveness, and efficiency (SEE), and disclosure and reporting (DR) through the relative importance index (RII) method. The result showed that DR is among the least practicing dimension having RII = 0.55, while PD and SEE have shown similar prevalence with RII = 0.70 and 0.69, respectively. Overall, the most practicing item in the PG was "the alignment of portfolios with objectives and strategy" whereas the lowest practicing item relates to the "completeness of project information distribution due to the multi-layered bureaucratic system." The findings of this study will guide the decision makers to take appropriate measures for enhancing the effectiveness of PG in Pakistan.