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The service‐dominant (S‐D) logic views supply chains as value co‐creation networks. These networks promote knowledge growth amongst network members via resource deployment and coordination. The exchange of knowledge and utilization of operant resources among the network members leads to co‐created service offerings and value proposals for the end‐users, with the ultimate goal of transforming end‐user experiences to perceptions of superior value‐in‐use. The purpose of this paper is to develop an illustration of the value co‐creation concept and use this illustration as guide to examine the research gaps that are yet to be tapped in the area where supply chain networks and S‐D logic intersects.

The literature on S‐D logic is reviewed and research gaps are identified and categorized in three specific groups.

Three categories of research gaps in S‐D logic and supply chain management (SCM) areas include: gaps in utilization of internal operant resources by suppliers, manufacturers, and intermediaries; gaps in knowledge exchange and operant resource utilization between suppliers, manufacturers, and intermediaries; and gaps in knowledge exchange and operant resource utilization between end‐users and value co‐creation network partners.

An illustration of the value co‐creation network from the supply chain perspective is presented in this paper. The illustration of the value co‐creation network provided the guidance to categorize various research gaps in the area of S‐D logic and SCM. This categorization offers a structure from which more systematic research may be produced. It is the authors' hope that the organization and guidance provided in the paper for specific research topics in the S‐D logic area can result in research streams that could potentially offer significant contributions to SCM theory development.

The purpose of this paper is to examine the impacts of (non-renewable and renewable) energy consumption and trade on environmental pollution in an environmental Kuznets curve (EKC) setting in Turkey for the 1965–2016 period.

Besides conventionally used unit root tests, Zivot–Andrews unit-root test is also employed to account for a possible structural break. To investigate the interrelationships among the variables, the autoregressive distributed lag and the vector error correction methodologies are employed.

The results verify the EKC hypothesis. Moreover, increases in trade and non-renewable energy consumption rise carbon emissions in long run, while renewable energy consumption reduces it in both short- and long-run. The causality analysis reveals that there are bi-directional long-run causalities between non-renewable energy consumption and carbon dioxide emissions, and between trade and carbon dioxide emissions. Additionally, the neutrality hypothesis is valid for the renewable energy consumption-income nexus in both short- and long-run. For the non-renewable energy consumption-income nexus, the neutrality hypothesis holds only in short-run and the conservation hypothesis holds only in long-run.

This is the first study which incorporates both renewable energy consumption and trade into its environmental pollution model for Turkey. Moreover, by investigating short- and long-run causalities among the employed variables, more robust policy implications are put forward. Lastly, this study employs a longer sample period and considers a structural break in its models.

The purpose of this paper is to investigate major event related terrorism and the resulting challenges that event professionals may face when hosting major events in cities as part of a destination marketing strategy.

The research was based in the UK due to the significant rise in terrorist activities that have taken place in its urban cities in recent years. The exploratory nature of this study utilised semi-structured interviews with UK event professionals, enabling a preliminary, in-depth investigation of the challenges that events professionals face as a result of major event related terrorism.

The research findings identify three challenges faced by event professionals when organising major events: knowledge and understanding in relation to major event related terrorism; the impact of major event related terrorism in terms of responsibility and accountability; and managing for major event related terrorism in budgetary terms.

The research is limited to the UK, other destinations will pose their own unique challenges when hosting and managing events. It is suggested that this research be evaluated against similar studies in other destinations. This is a preliminary study and each of the topics identified within the findings warrant further exploration in their own right.

The paper offers an insight into the challenges faced by event professionals in the UK when delivering major events as part of a destination marketing strategy. With the increase in major event related terrorism in cities the findings of this research are of relevance not only to event professionals but anyone with a role in destination and tourism development.

This study focuses on examining the impact of energy consumption, economic structure, population, and manufacturing output on the CO₂ emissions of selected emerging countries by utilizing the Structural Time Series Model (STSM). Based on the annual data ranging from 1970 to 2019, the model is built up using total primary energy consumption, GDP per capita, population and manufacturing value-added, and, finally, a stochastic Underlying Emission Trend as explanatory variables. STSM is extended by the introduction of the notion of Underlying Energy Demand Trend (UEDT) as a factor for exogenous effects, including development in technical progress, energy efficiency improvements, changes in human behaviors, economy, and environmental regulations. In this context, STSM and the notion of UEDT are implemented to form a forecasting model for CO₂ emissions of the selected emerging countries. The model discovers the significant influences of all selected variables of CO₂ emissions. The results suggest that the most forceful factor in CO₂ emissions is the total primary energy supply. Furthermore, while the long-term impact of economic growth on CO₂ emissions is negative for some emerging economies, it is positive for several others. The model also measures the long-term manufacturing value-added elasticity of CO₂ emissions in these emerging economies.

The purpose of this paper is to provide a survey of the empirical literature on environmental Kuznets curve (EKC) estimation of carbon dioxide (CO₂) emissions over the period of 1991–2017.

This survey categorizes the studies on the basis of power of income in empirical models of EKC. It has been hypothesized that the EKC shows an inverted U-shaped association between economic growth and CO₂ emissions.

For all the contexts, the results of EKC estimation for CO₂ emissions are inconclusive in nature. The reasons behind this discrepancy can be attributed to the choice of contexts, time period, explanatory variables, and methodological adaptation.

The future studies in this context should not only consider new set of variables (e.g. corruption index, social indicators, political scenario, energy research and development expenditures, foreign capital inflows, happiness, population education structure, public investment toward alternate energy exploration, etc.), but also the data set should be refined, so that the EKC estimation issues raised by Stern (2004) can be addressed.

By far, no study in the literature of ecological economics has focused on the empirical estimation of EKC for CO₂ emissions. This particular context has been used for this study, as CO₂ is one of the highest studied pollutants in the ecological economics, and especially within the EKC hypothesis framework.

This paper aims to assess the moderating role of foreign direct investment (FDI) on the effect of economic complexity on carbon emissions, considering other drivers of carbon emissions such as renewable energy use and economic growth, using data set spanning between 1990 and 2018 in BRICS nations.

This research aims to fill the gap in ongoing literature. Cross-sectional IPS and cross-sectional augmented Dickey–Fuller tests, fully modified ordinary least square, dynamic ordinary least square, fixed effect ordinary least square, Westerlund cointegration and method of moments quantile regression (MMQR) econometric approaches are applied.

The Westerlund cointegration outcomes disclosed long-run interconnectedness between carbon emissions and its drivers. Furthermore, MMQR outcomes disclosed that in each tail (0.1–0.90), economic growth and economic complexity contribute to upsurge in carbon emissions while in each quantile (0.1–0.90) renewable energy abate carbon emissions. Furthermore, we affirmed the pollution-haven and environmental Kuznets curve hypotheses across all quantiles (0.1–0.90). Finally, at all quantiles (0.1–0.90), the joint effect of both FDI inflows and economic complexity reduced carbon emissions. Furthermore, the panel causality outcomes disclosed that all the exogenous variables can predict carbon emissions. Based on the findings, BRICS nation’s policymakers should place a greater emphasis on FDI inflows because it aids in abating environmental degradation.

To the best of the authors’ knowledge, this is the first research to test the moderating role of FDI on the effect of economic complexity on carbon emissions. Hence, this research aims to fill the gap in ongoing literature.

The purpose of the paper is to identify how local populations, particularly at the municipal and village levels, can enhance their capacity to prepare and respond more effectively and efficiently to the logistic challenges that they face in the aftermath of a natural disaster.

Using a phenomenological approach, a qualitative research study was conducted from an interpretative, constructivist perspective. Through a series of semi‐structured interviews the researchers gathered stories about the experiences of local responders at municipal level in the capital city region of the Republic of the Philippines in the aftermath of a specific natural disaster event (Typhoon Ondoy – September 2009). A number of key differences between the espoused strategies expressed in disaster management legislation and the actual experiences of local people on the ground were identified and, as a result, a conceptual model was developed that, if implemented, would enhance the capacity of local populations to prepare and respond in a more efficient and effective manner.

Results from the study indicate that the ability of local populations to contribute to the logistic preparation and response processes has been considerably undervalued and underutilised. A revised model is therefore developed that better incorporates their potential contribution to the management of both the demand and supply sides that would lead to swifter, more accurate, and more efficient logistic response mechanisms.

The developing canon of humanitarian logistic literature has, to date, been relatively silent on the subject of the contribution of the local population to the overall logistic management challenge. The paper provides important insights into the issues on which the government of a developing country could usefully focus attention in their approach to natural disaster preparedness and response, and it offers a conceptual model for future testing and evaluation.

This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.

The purpose of this paper is to evaluate and compare the protective, anticorrosion behaviors and electrochemically synthesis of poly(2-chloroaniline) (PCANI) and poly(2-chloroaniline-co-aniline) P(CANI-co-ANI) films on thin zinc–iron plated carbon steel (CS).

Zinc–iron (ZnFe) alloy plating was successfully achieved on CS applying 3 mA constant current value. The PCANI and P(CANI-co-ANI) films on ZnFe-plated CS electrode were synthesized by cyclic voltammetry technique using monomer(s) containing 0.20 M sodium oxalate solution. The CS/ZnFe electrodes with and without PCANI or P(CANI-co-ANI) films were characterized using SEM and anodic linear sweep voltammograms. The anticorrosive behaviors of uncoated and coated electrodes were studied in 3.5 per cent NaCl solution by corrosion techniques which include open circuit potential measurements, the anodic polarization curves and alternative current electrochemical impedance spectroscopy (EIS) technique.

The protection efficiency values (E per cent) for CS/ZnFe, ZnCS/ZnFe/PCANI and CS/ZnFe/P(CANI-co-ANI) electrodes were calculated as 71.05, 84.53 and 92.79, respectively, after 168 h of immersion time. The results showed that P(CANI-co-ANI) coating on ZnFe-plated CS electrode exhibited higher corrosion resistance and provided better barrier property in comparison with PCANI coating and ZnFe alloy plating, in longer exposure time.

A number of reports on the synthesis and characterization of PANI have appeared in the literature during the past decade, but there is no such publication of PCANI. At the same time, the synthesis of PCANI onto the surface of metal alloy coating being the first of this kind, no such proceedings have been reported in the literature so far.