The Study on the Effectiveness of Sustainable Customer Relationship Management: Evidence from the Online Shopping Industry

Sustainable development integrates business, environmental, and social objectives into a unified effort to achieve a common goal. Sustainable customer relationship management (CRM) combines company strategy, customer-focused business processes, and computer technologies. From the consumer's perspective, it lowers psychological, energy, time, and other costs;from the company's perspective, it offers a means of engaging with customers to build lasting and reliable relationships. The sustainable CRM program provides advantages to businesses in various industries, particularly online commerce. It alludes to a comprehensive strategy that promotes solid interactions between buyers and sellers of goods and services. Since current customer retention is less costly than new customer attraction in competitive markets, especially online shopping, identifying the factors affecting relationship management with stable customers is essential. This investigation intends to evaluate the effect of the use of management information systems (MIS), as well as insights on employee behavior and knowledge, and customer behavior (satisfaction and loyalty), on the effectiveness of sustainable CRM in online shopping. The model is validated using the PLS–SEM technique, and study sample of 293 employees and managers from private organizations. According to the results, the MIS, employee behavior and knowledge, customer satisfaction, and customer loyalty influence the effectiveness of sustainable CRM in online shopping. Furthermore, employee behavior and knowledge positively moderate the relationship between customer loyalty and the effectiveness of sustainable CRM. However, the moderating role of employee behavior and knowledge on customer satisfaction and the effectiveness of sustainable CRM is not confirmed. Overall, taking these characteristics into account might help organizations to take significant steps toward increasing the efficacy of sustainable CRM.

Macroeconomic and Uncertainty Shocks' Effects on Energy Prices: A Comprehensive Literature Review

GDP, monetary variables, corruption, and uncertainty are crucial to energy policy decisions in today's interrelated world. The global energy crisis, aggravated by rising energy prices, has sparked a thorough analysis of its causes. We demonstrate the significance of categorizing research by influence channels while focusing on their implications for energy policy decisions. We investigate the growing number of studies that use GDP, inflation, central banks' characteristics, corruption, and uncertainty as critical factors in determining energy policies. Energy prices fluctuate because energy policies shift the supply–demand equilibrium. We categorise the effects and show that GDP, economic policy uncertainty, and, most notably, specific economic conditions and extreme events play a significant role in determining energy prices. We observed that energy consumption, GDP growth, and energy prices have a bidirectional, causal relationship. Still, the literature has not established which causative direction is the most significant. Taxes, interest rates, and corruption also significantly determine energy prices, although the origins of corruption have not been adequately examined. Lastly, uncertainty generally increases energy costs, but this relationship requires additional research in terms of the features of countries, conditions, and, most importantly, the theoretical backgrounds used.

Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices

The cost of electricity and gas has a direct influence on the everyday routines of people who rely on these resources to keep their businesses running. However, the value of electricity is strongly related to spot market prices, and the arrival of winter and increased energy use owing to the demand for heating can lead to an increase in energy prices. Approaches to forecasting energy costs have been used in recent years;however, existing models are not yet robust enough due to competition, seasonal changes, and other variables. More effective modeling and forecasting approaches are required to assist investors in planning their bidding strategies and regulators in ensuring the security and stability of energy markets. In the literature, there is considerable interest in building better pricing modeling and forecasting frameworks to meet these difficulties. In this context, this work proposes combining seasonal and trend decomposition utilizing LOESS (locally estimated scatterplot smoothing) and Facebook Prophet methodologies to perform a more accurate and resilient time series analysis of Italian electricity spot prices. This can assist in enhancing projections and better understanding the variables driving the data, while also including additional information such as holidays and special events. The combination of approaches improves forecast accuracy while lowering the mean absolute percentage error (MAPE) performance metric by 18% compared to the baseline model.

Appropriateness of EToU electricity tariff program for industrial type consumers: an investigation of cost benefit

In mitigating the peak demand, the energy authority in Malaysia has introduced the enhanced time of use (EToU). However, the number of participants joining the programs is less than expected. Due to that reason, this study investigated the investment benefit in terms of electricity cost reduction when consumers subscribe to the EToU tariff scheme. The significant consumers from industrial tariff types have been focused on where the load profiles were collected from the incoming providers' power stations. Meanwhile, ant colony optimization (ACO) and particle swarm optimization (PSO) are applied to optimize the load profiles reflecting EToU tariff prices. The proposed method had shown a reduction in electricity cost, and the most significant performance has been recorded congruently. For a maximum 30% load adjustment using ACO optimization, the electricity costs have been decreased by 10% (D type of tariff), 16% (E1 type of tariff), 9% (E2 kind of tariff), and 1.13% (E3 type of tariff) when compared to the existing conventional tariff. The cost-benefit of the EToU tariff switching has been identified where the simple payback period (SPP) is below one year for all the industrial types of consumers.

Overview of Solar–Wind Hybrid Products: Prominent Challenges and Possible Solutions

Solar and wind power systems have been prime solutions to the challenges centered on reliable power supply, sustainability, and energy costs for several years. However, there are still various challenges in these renewable industries, especially regarding limited peak periods. Solar–wind hybrid technology introduced to mitigate these setbacks has significant drawbacks and suffers from low adoption rates in many geographies. Hence, it is essential to investigate the challenges faced with these technologies and analyze the viable solutions proposed. This work examined solar–wind hybrid plants’ economic and technical opportunities and challenges. In the present work, the pressing challenges solar–wind hybrids face were detailed through extensive case studies, the case study of enabling policies in India, and overproduction in Germany. Presently, the principal challenges of solar–wind hybrids are overproduction, enabling policies, and electricity storage. This review highlights specific, viable, proposed solutions to these problems. As already recorded in the literature, it was discovered that academic research in this space focuses majorly on the techno-economic and seemingly theoretical aspects of these hybrid systems. In contrast, reports and publications from original equipment manufacturers (OEMs) and engineering, procurement, and construction engineers (EPCs) are more rounded, featuring real-life application and implementation.

Transformation of Energy Markets: Description, Modeling of Functioning Mechanisms and Determining Development Trends

Undoubtedly, the development of the renewable energy sector is linked to the goals of sustainable development [16,17,18,19], where the greatest emphasis is placed on caring for the environment and transitioning from classical energy sources to renewable and non-carbon sources. The authors emphasize the importance of a harmonized energy transition process, noting that the suspension of energy transformation processes may move from one region to the entire member state, or that it is possible for the economy of one of the countries, or a group of countries, to undergo a serious economic crisis. [...]eventualities would bring some countries back to the starting point and jeopardize the future of the entire EU energy project [24]. In [28], the authors focus on energy consumption in health care facilities, trying to set the determinants of electricity and thermal energy costs in relation to the size and intensity of work in Polish clinics. The authors of [29] deal with factors determining the demand for energy consumption from renewable sources in European countries.

Optimization and Integration of Renewable Energy Sources with Regional Tourism Potentials to Improve the Welfare of Local Communities

Indonesia is a country with a tropical climate and has tens of thousands of islands. One of the challenges is that archipelagic countries generally have limited local resources and high energy import costs. Renewable energy technologies in most islands are often not running and are unsustainable due to the many problems involved, one of which is the lack of clarity on management and generating assets. As a result, power plants generally only run for a short time and do not provide electrical energy for the community. In addition to the unavailability of electricity, the COVID-19 virus certainly also affects activities, especially people who rely heavily on the tourism sector as their main livelihood. Therefore, it is necessary to explore how an island could survive in this force majeure situation, both from the sustainability of renewable energy and the tourism sector. This research aims to explain what factors affect the sustainability of renewable energy in supplying electricity to the community in the long term and will present the interrelation between the tourism sector and the presence of renewable energy technology. The method used is an in-depth interview and questionnaire with a Likert scale. The research was conducted on the island of Mecan and the obtained data were simulated in the form of CLD (Causal Loop Diagram). The results indicate that renewable energy sustainability on Mecan Island has made access to electricity available throughout the day and has improved the welfare of residents.

A Sustainability Improvement Strategy of Interconnected Data Centers Based on Dispatching Potential of Electric Vehicle Charging Stations

With the rapid development of information technology, the electricity consumption of Internet Data Centers (IDCs) increases drastically, resulting in considerable carbon emissions that need to be reduced urgently. In addition to the introduction of Renewable Energy Sources (RES), the joint use of the spatial migration capacity of IDC workload and the temporal flexibility of the demand of Electric Vehicle Charging Stations (EVCSs) provides an important means to change the carbon footprint of the IDC. In this paper, a sustainability improvement strategy for the IDC carbon emission reduction was developed by coordinating the spatial-temporal dispatch flexibilities of the IDC workload and the EVCS demand. Based on the Minkowski sum algorithm, a generalized flexible load model of the EVCSs, considering traffic flow and Road Impedance (RI) was formulated. The case studies show that the proposed method can effectively increase the renewable energy consumption, reduce the overall carbon emissions of multi-IDCs, reduce the energy cost of the DCO, and utilize the EV dispatching potential. Discussions are also provided on the relationship between workload processing time delay and the renewable energy consumption rate.

Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

Energy efficiency has become a major concern for manufacturing companies not only due to environmental concerns and stringent regulations, but also due to large and incremental energy costs. Energy-efficient scheduling can be effective at improving energy efficiency and thus reducing energy consumption and associated costs, as well as pollutant emissions. This work reviews recent literature on energy-efficient scheduling in job shop manufacturing systems, with a particular focus on metaheuristics. We review 172 papers published between 2013 and 2022, by analyzing the shop floor type, the energy efficiency strategy, the objective function(s), the newly added problem feature(s), and the solution approach(es). We also report on the existing data sets and make them available to the research community. The paper is concluded by pointing out potential directions for future research, namely developing integrated scheduling approaches for interconnected problems, fast metaheuristic methods to respond to dynamic scheduling problems, and hybrid metaheuristic and big data methods for cyber-physical production systems.

The Investigation of Key Factors in Polypropylene Extrusion Molding Production Quality

This study took food-grade polypropylene packaging products as the research project and discussed how to control the polypropylene extrusion sheet thickness and vacuum thermoforming quality and weight. The research objective was to find the key factors for reducing costs and energy consumption. The key aspects that may influence the polypropylene extrusion molding quality control were analyzed using literature and in-depth interviews with scholars and experts. These four main aspects are (1) key factors of polypropylene extrusion sheet production, (2) key factors of the extrusion line design, (3) key factors of polypropylene forming and mold manufacturing, and (4) key factors of mold and thermoforming line equipment design. These were revised and complemented by the scholar and expert group. There are 49 subitems for discussion. Thirteen scholars and experts were invited to use qualitative and quantitative research methods. A Delphi questionnaire survey team was organized to perform three Delphi questionnaire interviews. The statistical analyses of encoded data such as the mean (M), mode (Mo), and standard deviation (SD) of various survey options were calculated. Seeking a more cautious research theory and result, the K-S simple sample test was used to review the fitness and consistency of the scholars’ and experts’ opinions on key subitem factors. There are ten key factors in the production quality, including “A. Main screw pressure”, “B. Polymer temperature”, “C. T-die lips adjustment thickness”, “D. Cooling rolls pressing stability”, “E. Cooling rolls temperature stability”, “F. Extruder main screw geometric design”, “G. Heating controller is stable”, “H. Thermostatic control”, “I. Vacuum pressure”, and “J. Mold forming area design”. The key factors are not just applicable to classical polypropylene extrusion sheet and thermoforming production but also to related process of extrusion and thermoforming techniques in expanded polypropylene (EPP) sheets and polylactic acid (PLA). This study aims to provide a key technical reference for enterprises to improve quality to enhance the competitiveness of products, reduce production costs, and achieve sustainable development, energy savings, and carbon reductions.

Watchful Eye

"Adapting strategies for the future of work, supply chain resilience and digital maturity can help manufacturers keep pace and drive performance amid strong economic demand," said authors of one U.S. manufacturing industry research report developed by Deloitte. Predictive maintenance Automating the process of predicting problems during the manufacturing process is certain to reduce downtime and increase efficiencies on the shop floor. Sustainability Economically and environmentally sustainable business practices have become a business imperative as energy and materials costs rise, regulations tighten, and consumers and investors are keyed in on sustainable brands and business practices.

Optimization of e-Mobility Service for Disabled People Using a Multistep Integrated Methodology

The penetration of e-mobility is growing thanks to the European guidelines on climate preservation regarding the reduction in CO2 emission. Governments are adapting their economic policies with the aim to incentivize e-mobility. At the same time, with a view to equality and accessibility, countries are working to introduce e-mobility services also for people with disabilities in order to improve the quality of their lives. The paper reports the deployment of an e-mobility service for persons with disabilities carried out in a project financed by Sapienza University of Rome. The project includes a feasibility study and a cost–benefit analysis in order to identify the optimal solution from a technical and environmental point of view for a sustainable e-mobility service for people with reduced mobility. A methodology to design a service based on optimal routes and electric vehicles with respect to energy consumption, time travel, energy and vehicle costs and quality of service is proposed. The 5-step methodology calculates the most energy-efficient routes and defines the optimal charging schedule, taking into account charging points dislocated along the routes and choosing vehicle typologies with the best performance based on economic evaluations. A software was developed to automatize the methodology.

A Fuzzy Grouping Genetic Algorithm for Solving a Real-World Virtual Machine Placement Problem in a Healthcare-Cloud

Due to the large-scale development of cloud computing, data center electricity energy costs have increased rapidly. Energy saving has become a major research direction of virtual machine placement problems. At the same time, the multi-dimensional resources on the cloud should be used in a balanced manner in order to avoid resources waste. In this context, this paper addresses a real-world virtual machine placement problem arising in a Healthcare-Cloud (H-Cloud) of hospitals chain in Saudi Arabia, considering server power consumption and resource utilization. As a part of optimizing both objectives, user service quality has to be taken into account. In fact, user quality of service (QoS) is also considered by measuring the Service-Level Agreement (SLA) violation rate. This problem is modeled as a multi-objective virtual machine placement problem with the objective of minimizing power consumption, resource utilization, and SLA violation rate. To solve this challenging problem, a fuzzy grouping genetic algorithm (FGGA) is proposed. Considering that multiple optimization objectives may have different degrees of influence on the problem, the fitness function of the proposed algorithm is calculated with fuzzy logic-based function. The experimental results show the effectiveness of the proposed algorithm.

Characterization of Technological Innovations in Photovoltaic Rural Electrification, Based on the Experiences of Bolivia, Peru, and Argentina: Third Generation Solar Home Systems

The electrification of isolated homes in rural areas without access to the electric grid has been achieved in part using solar energy transformed into electricity through Photovoltaic (PV) equipment known as Solar Home Systems (SHSs), which has been widely disseminated throughout the world. The use of SHSs in rural electrification projects has been studied from 1980 to date, they have been incorporating advances and technological innovations successively. Through the review of documents on PV projects, articles, and technical reports, it has been possible to identify the changes in the main components of the SHS and the typical configurations, systematizing them in a discrete timeline. Thereby, this article characterizes three generations of SHSs and highlights their differences. The first generation is fully valid between 1980–1995, the second generation in 1995–2010, and the third generation from 2005 to date, which overlaps the beginning. In any case, the time limits in each period are only referential. The later generation, Third Generation Solar Home Systems (3G-SHSs), is highly efficient, uses LED lamps, lithium batteries, microelectronic control, and plug and play connections. Indeed, this equipment can be self-managed by the user and reflects the technology’s high reliability by a minimum maintenance service in situ. Furthermore, their lower costs make access to electricity more affordable for the last mile population. The present research offers a detailed technological and operational characterization of the 3G-SHSs to show the most relevant aspects of support to project developers, planners, and decision-makers to achieve the Sustainable Development Goal (SDG) 7.

Investigating the role of electric vehicle knowledge in consumer adoption: evidence from an emerging market

Purpose>The use of electric vehicles has received popularity as alternative fuel vehicles to reduce greenhouse gas emissions and energy cost, which are expected to perform a crucial role in the near future of emerging mobility markets. The purpose of this empirical study is to analyse the role of electric vehicle knowledge in predicting consumer adoption intention directly and indirectly in the backdrop of an emerging market.Design/methodology/approach>The study approached an extended version of “Technology acceptance model” (TAM) based on the integrated framework of “knowledge-beliefs-intention”. The model was tested via direct and indirect path analyses with the data collected from Indian respondents using an online survey.Findings>The results indicate the robustness of the present research model, which shows that consumer adoption is significantly driven by electric vehicle knowledge, perceived usefulness, perceived ease of use and perceived risk. Electric vehicle knowledge has emerged as the most powerful cognitive measure, which directly affects the adoption intention along with the measures of “TAM”. Additionally, this also poses a higher indirect effect on adoption intention in the integrated model.Research limitations/implications>The study has focused on potential young and educated consumers, which may not be warranted to generalise the research findings, while youth or millennials are more receptive to adopt innovative and clean technology products like electric vehicle. Based on the findings, implications are offered for encouraging electric vehicles in the backdrop of emerging automobile markets.Originality/value>Concerning this cognitive phenomenon of knowledge, scant literature has been explored the role of subjective knowledge in consumer adoption for electric vehicles, particularly in the emerging markets like India. Thus, the present study analyses how consumers' knowledge about electric vehicle affects their decision to adopt this in the near future of Indian zero-emission mobility market.

Change in the Affordability of Owner-Occupied Housing in the Context of Rising Energy Prices

Household energy constitutes an important share of affordable housing. Unaffordable housing and inadequate household energy represent a new dimension of poverty. Connections between energy, housing affordability and well-being are still under-researched. Building on housing affordability framework, this study explores the magnitude in changes in affordability of acquisition and use of an apartment between January 2018 and January 2022. Over the last four years, the real estate market in Europe has changed significantly. This paper deals with primary data for the Czech Republic, where acquisition prices of residential real estate increased depending on the region in the range of 50 to 120%. Since January 2022, there has been a sharp rise in energy prices and a tightening of conditions for the acquisition of mortgage loans. All these factors affect the standard of living in the Czech Republic. The article quantifies the magnitude of this change by calculating shares of total housing costs to total average net household income for the period January 2018 and January 2022. It is found that the affordability of owner-occupied housing in the Czech Republic has deteriorated and part of the middle class will be forced to move to the rental housing sector, multifamily housing and sharing. Finally, we argue that energy poverty needs to be considered in addressing the government housing policies. The aim of the article is to analyze the changes that have taken place in the real estate market over the last four years in relation to the growth of total housing costs and energy costs associated with housing.

Critical Assessment of Feed-In Tariffs and Solar Photovoltaic Development in Vietnam

Vietnam became the world’s third largest market for solar photovoltaic energy in 2020. Especially after the Vietnamese government issued feed-in tariffs for grid-connected solar photovoltaic systems, the installed capacity of solar photovoltaic applications exploded in 2019. From studies carried out in the relevant literature, it can be said that support policies are highly important for the initial development of the renewable energy industry in most countries. This is especially true in emerging countries such as Vietnam. This paper reviews the feed-in tariffs issued and deployed in different regions of Vietnam for grid-connected solar photovoltaic applications. Moreover, the paper takes a closer look at the costs of electricity production from these systems in relation to the feed-in tariffs issued in Vietnam. The results show that the gap between the levelized cost of electricity and the feed-in tariff for solar photovoltaic electricity is relatively high, particularly in regions with a lower irradiation potential.

Steering Renewable Energy Investments in Favor of Energy System Reliability: A Call for a Hybrid Model

The global increase in electricity supply volatility due to the growing share of intermittent renewable energy sources together with recent extreme weather events draws attention to energy system reliability issues and the role of renewable energy sources within these systems. Renewable energy deployment strategies have already become a key element in debates on future global energy systems. At the same time, more extensive use of renewable energy sources implies a higher dependence on intermittent power, which puts the reliability of the electricity system at risk. Policymakers are introducing measures to increase the reliability of energy systems. Paradoxically, support for renewable energy and analyses of energy system reliability have been dealt with by two different and rarely overlapping research approaches. As a result, renewable energy promotion has often been designed without accounting for system reliability. To our knowledge, a model that captures those investment incentives and allows for tuning such financial support does not exist. This paper introduces a hybrid model that can potentially steer renewable energy investments in favor of energy system reliability. We demonstrate the idea of reliability-based support for renewable energy sources in action using a stylized case. Depending on the complementarity of different renewable energy power outputs available in the system, such reliability-based support can substantially reduce the necessity for greater backup capacity, can cut the overall costs of the energy system, and can reduce its environmental footprint.