Sustainability and Information Systems in the Context of Smart Business: A Systematic Review

Abstract

In recent years, calls have increased for adherence to standards that ensure sustainability, including the global initiative presented by the United Nations with 17 Sustainable Development Goals (SDGs) to ensure a more sustainable future. Achieving these goals is extremely important, as institutions have sought to integrate technology, especially business intelligence, into their operations to ensure their achievement. This study aims to provide a systematic literature review of the intersection of information systems and sustainability in business intelligence. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was utilized to select high-quality studies from various databases, including ScienceDirect, IEEE Xplore, and Scopus, to be included in this review. The methodology resulted in 32 studies taxonomized into four main categories covering different aspects of the intersection of information systems and sustainability. This study discusses integrating information systems and sustainability in various sectors, such as tourism, health, urban, and other sectors, with different technologies, such as Blockchain, IoT, Industry 4.0, and other innovations. Moreover, the information system types implemented to support sustainability practices in different domains are highlighted.

1. Introduction

As the information technology sector grows exponentially and spreads to other fields, the need for sustainable means to manage technology also increases. For proper and efficient integration of information systems into other disciplines, environmental aspects must be considered, which is the current direction many are taking within their research. This includes both environmental considerations and system durability. Sustainable software has been a topic of discussion interchangeably with software sustainability; this is believed to be a result of researchers not distinguishing between the two similar concepts [1], with further focus being given to the environmental aspects of sustainability over others, such as the long duration of the software system [2]. Both aspects must be considered to achieve responsible usage of software systems in this day and age.

Sustainability for software, as defined by researchers in [3], refers to the environmental aspects of sustainable software. This can include several dimensions; however, more focus is given to the environmental aspect, which involves resources that the software uses up and the direct pollution and waste that results from that usage on ecosystems and nature [4]. This definition will be used when referring to sustainable software for this study. Software sustainability follows the definition of sustainability in software, as defined by the same study, which means software that is able to sustain an adequate level of durability for its purpose. Both concepts are explored in this study in detail, with direct mentions of the literature that discusses each.

The integration of information systems and technology has spread to countless fields and disciplines, with many falling under the area of intelligent business. Business, in general, encompasses many domains, all of which impact the environment in one way or another. The main goal of the system also affects longevity to a certain extent. As many intertwined aspects affect software sustainability, this study explores both aspects and how they have been discussed in the literature.

The rapid expansion of the information technology sector into various fields has necessitated sustainable management practices for technology integration. As businesses increasingly rely on advanced information systems, ensuring these technologies are environmentally sustainable and resilient over time is crucial. This dual focus is vital for minimizing ecological footprints and enhancing the longevity and effectiveness of technological solutions. The sustainable integration of information systems presents significant challenges.

This study provides a comprehensive systematic literature review on the intersection of information systems and sustainability within the context of smart business. Employing the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) methodology. First, this review highlights the role of various technologies such as Blockchain, the Internet of Things (IoT), Industry 4.0, etc., and it explores how information systems can support sustainable practices across different sectors. Next, it analyzes distinct types of information systems and their role in supporting sustainability. This dual focus helps us understand how technological advancements can be leveraged to meet sustainability goals effectively. Furthermore, it discusses the fundamental pillars of sustainability and how these studies contribute to achieve the SDGs. Lastly, it explores the technologies adopted by the reviewed studies and their pivotal roles in sustaining the smart business

Consequently, understanding the implications of this study is crucial for researchers, practitioners, and policymakers. It, thus, outlines what is often referred to as software sustainability to provide better contours for future research and practical application. These findings align with the global effort of attaining the 17 United Nations Sustainable Development Goals, also known as the SDGs, and prove information systems’ role in improving sustainable development processes’ effectiveness, accountability, and effectiveness. In addressing these critical areas, this study provides valuable information for ongoing academic debates and relevant recommendations for augmenting the sustainability of information system development across different fields. Therefore, the sustainable development model guarantees that numerous initiatives are integrated with technology to enhance environmental, social, and economic goals in the long term.

The research was formulated and guided by the following research questions:

RQ1: What are the current trends in the information systems with sustainability in smart businesses?

RQ2: What technologies are being employed in the information systems field to enhance sustainability?

2. Systematic Literature Review (SLR) Protocol

This study follows a systematic literature review (SLR) process to review the intersection of sustainability and information systems in intelligent business. The search process began by clearly defining the primary goals of our review. First, to highlight the role of information systems in promoting sustainability across various sectors, specifically within smart businesses and in alignment with the United Nations’ 17 Sustainable Development Goals (SDGs). Furthermore, we aimed to examine the specific information system technologies that contribute to sustainability. Then, the goals were broken down into sub-goals to identify a search string that would align with the review objective very well. As mentioned earlier, in the systematic review processes, this study established the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol [5], which describes the review’s rationale, hypothesis, and planned methods. This protocol is backed by many esteemed universities, including the University of Oxford and includes a set of rules and sequential steps to follow during the review process. This review follows the main steps of the PRISMA protocol, directly referenced from their official website (Figure 1).

2.1. Information Sources

The search process starts by selecting the online databases to extract literature for review using the predefined search string. In this review, the following databases were chosen: (1) ScienceDirect, (2) IEEE Xplore, and (3) Scopus. These databases were chosen due to their comprehensive collection of journals and the high caliber of research they offer.

2.2. Search Strategy and Search String

The search was conducted on 7 October 2023 with the following search string: (“Sustainability” AND “Information Systems” AND “Smart Business”), used to select the studies from the aforementioned databases.

2.3. Inclusion Criteria

In our systematic literature review, we carefully set up the appropriate criteria to select the best studies for our purposes. These criteria help us sift through studies effectively by filtering out articles that do not meet our needs, with the remaining articles matching our study’s chosen topics.

Table 1. Inclusion criteria.

IC	Research or Review Articles
IC1	Published in the English language
IC2	The study has been published between 2019 and 2023
IC3	Address the utilization of information systems in the context of sustaining smart businesses sector

outlines the inclusion criteria (IC) that articles must follow to be selected for further screening in our study. Studies that did not fall under these criteria were consequently excluded from the screening phase.

2.4. Study Selection

The selection process began by applying the predefined search string across multiple databases, identifying 154 studies. After these studies were retrieved, 7 duplicate entries were removed, leaving 147 unique studies. The remaining studies were screened based on their titles and abstracts to assess whether they met the predefined inclusion criteria. This step resulted in the exclusion of 112 studies, 35 of which remained for further evaluation. Subsequently, these 35 studies were subjected to a complete full text review to confirm their eligibility. This phase led to the exclusion of 3 studies that did not meet the full inclusion criteria. Ultimately, 32 studies passed this final assessment and formed the final set of articles to review.

3. Taxonomy Results

This section examines the relationship between information systems, smart business and sustainability. We conducted a detailed analysis of the final set of selected studies, focusing on shared themes and insights, by categorizing the reviewed literature into four distinct themes. These four categories are 3.1. Information Systems for Smart Business Sustainability Across Sectors, 3.2. Information System Types to Support Sustainability, 3.3. Sustainable Development Components, and 3.4. Information System Technology Employed for Sustainability. Each category explores different aspects of sustainability across various domains. Section 3.1 highlights the smart technologies and sustainability within six distinct sectors. Furthermore, Section 3.2 discusses different types of information systems and how they support sustainability. Section 3.3 highlights the pillars of sustainability and discusses how the studies align with the UN SDGs. Lastly, Section 3.4 discusses the adopted technologies in the studies and what are their roles in sustaining the smart business. We found that each category from the four can be further divided into subcategories to reflect the complete picture of this critical multidisciplinary topic.

3.1. Information Systems for Smart Business Sustainability across Sectors

This section concerns information systems and their role in sustaining smart business in different sectors. Most of the categories seem to relate to businesses and Industry 4.0, which is no surprise when discussing the sustainability of smart technology in general (see Figure 2). The following sections detail how each category can be noted and discussed in the literature collected through our study.

3.1.1. Urban Planning and Improvement

One prevalent topic regarding smart technology in the literature is smart cities, which have emerged as a possible solution to the increasingly worsening urbanization problem worldwide [6]. With overpopulation and increasing urban migration, a smarter and more advanced way of managing cities has become necessary for communities and countries to progress. This category included 4 out of 32 studies.

A systematic review and analysis provided in [7] identified several themes and topics about smart cities and explored how research on smart cities has evolved by analyzing more than 100 literature sources. While ref. [8] focused on reviewing China’s promotion of smart cities and smart industrial parks as solutions for sustainable development and the transition into lowering carbon emissions by analyzing policy histories and national projects. This review revealed that China has rapidly developed national pilots and has seen opportunities for integrated systems, innovative decision tools, and smart governance frameworks.

Another study discusses the implementation specifics of sustainable smart technologies in city management, such as [9], where the authors propose a model for energy sustainability in smart cities using Internet of Things (IoT) technology and a deep extreme learning machine (DELM). This study explores the use of DELM to create a predictive model for predicting the hourly electrical energy output of a combined cycle power plant. The model includes data acquisition, preprocessing, and an application layer using DELM for prediction. The performance was evaluated using statistical measures, and it shows that the DELM achieves a high prediction accuracy of 98.6%, which can help in optimizing the city and its efficiency.

Furthermore, the study [10] sheds light on rural areas to promote sustainable development. This study provides an overview of the current adoption of smart technologies in rural regions, including energy management, [11], farming, education, business, healthcare, and governance. It analyzes the characteristics of rural regions and the potential for smart technologies to enhance development by increasing agricultural production, improving access to education and healthcare, optimizing business operations, and addressing gaps in public services. However, more research that explicitly targets the rural context needs to be conducted.

3.1.2. Tourism Sector

The relationship between tourism and sustainability is complex [12]. It is constantly being researched extensively within both the tourism and sustainability sectors [13], and using smart technology in this field is an opportunity to address many of the issues and challenges associated with the concept of “sustainable tourism” [14]. This category included 4 out of 32 studies.

From the available literature, sustainable practices in tourism via smart technology are still in their development phase, as exhibited by the many studies that aimed to offer a guideline or framework concerning a specific issue or subfield within tourism in that context. An example is the work of [15], in which the authors set out to create guidelines for implementing smart tourism using a case study in Spain. Similarly, another case-based study in Spain was conducted by [16], in which a framework was built to assess the indicators of smart technology for sustainable tourism in coastal destinations. By using a case study similar to the previous two studies, ref. [17] introduced a review study that assesses current and potential progress in this field.

3.1.3. Supply Chain Sector

Supply chains play a pivotal role in local business and global economics [18], as seen by the worldwide setback during the quarantine of COVID-19. This increased importance is the driving force of the advancements within the field, among which is integrating smart technologies in managing supply chain sectors. This review covered 5 out of 32 studies on this topic.

Similar to the previous sections, this topic is still in its earlier phases of advancement. As such, the studies in this area go primarily in one of two ways: either a review/empirical study/research into building frameworks or guidelines to facilitate the integration of sustainable smart technologies in supply chain management. Among the first category are studies [19,20,21] with each study discussing a specific aspect, whether it is the smart technology being investigated in supply chain management or the subfields of this area. The first study by [19] provides an overview of the impact of Industry 4.0 on supply chain management in general and blockchain technology in particular. Their review was performed systematically, where three initial topics were extracted from the literature as focal points of the review study to be investigated within four main areas. This review is especially informative to those seeking to tackle the research gaps in this field, as the authors discuss in lengthy detail the many areas in which the current literature lacks, and they also organize these points into five main areas of improvement. For the second study, conducted by [20], a more focused topic, agricultural supply chain management, was reviewed. This study examines the effects of Industry 4.0 mainly on sustainable agricultural supply chain performance (SASCP) by analyzing data collected from 262 food processing organizations in India. Although not necessarily a review study, the study also offers excellent insight into the current literature and the shortcomings of the research in this study that they have faced throughout their work. The third study [21] focuses on the assumption that AI helps supply chains adapt to changing conditions and make better decisions, especially for smaller businesses, which are the target of this study. They use a hybrid method to investigate how AI affects risk management in these smaller businesses, which is a method they recommend further in future works to address the multitopic nature of the data in supply chain management. They concluded that AI influences how a supply chain is restructured, which in turn affects agility in the chain and how different methods show consistent results; hence, there is a need for a hybrid method for such collaborative conclusions.

The second category included two studies from the literature we collected. A study by [22] focused on how innovative technologies, like the Internet of Things, can make supply chains more intelligent. The research also explores how smart technology (in this case, the IoT) and big data analytics can improve decision making and efficiency in supply chains, a sentiment shared by many studies mentioned earlier. The effects of integrating smart technology in supply chains are also evident in this study [23], which examines how seaports have transformed from essential transportation hubs to vital components of global supply chains, often referred to as fifth-generation (5G) ports, smart ports, or ports 4.0. These terms reflect that ports are now highly advanced and technologically integrated entities. To better understand these dynamics, this study develops a conceptual model to explain how adopting Industry 4.0 technologies shapes the evolution of seaport business models. This model is then tested through a case study on the port of Barcelona to assess its validity and relevance.

3.1.4. Integrated Manufacturing and Industry 4.0

Industry 4.0 is a recurring topic when researching anything pertaining to smart technologies, and this topic is no exception when considering sustainable smart systems. A sizable number of studies within the literature have investigated industries in different fields under the umbrella term “Industry 4.0”. In this category, we found 7 out of 32 studies.

Most of the studies in this category consider Industry 4.0 as a whole and discuss various smart technologies in general; however, the works of [24,25] focus specifically on blockchain technology. The first study is a review of blockchain technology within the context of the automotive industry, with an extensive look into the potential of this technology in enhancing many aspects of the automotive industry, including the manufacturing process. The authors identify many points of future research and current weaknesses that can be addressed by the research community further. For the second study, the authors implement a blockchain-based marketplace to investigate the viability of blockchain technology within a digitalized market for achieving sustainable development goals (SDGs). The authors consider the results of this experiment satisfactory.

Other topics that fall under this category include construction, as shown in the study conducted by [26]. In this study, the authors address the lack of research on sustainable smart technologies, specifically within the construction field, by establishing a framework to address the sustainable implementation of such technologies. The framework was used as a practical case study and proved valuable and positive. Similarly, a study specifically targeting the manufacturing industry was conducted by [27].

Many authors have chosen to highlight the potential and future directions of sustainable smart technology in Industry 4.0 [28,29,30]. The first study uses bibliometric analysis to provide a scientific view of the relationship between Industry 4.0 and sustainability through a highly analytical literature review. The second study notes the growing potential of intelligent organizations, and the authors, therefore, propose a synthetic index called the Power of Smart Organizations index (PSOI) to monitor and support the development of these intelligent organizations and enhance the competitiveness and sustainability of countries, with a focus on the EU. This index integrates microeconomic (organization-level) and macroeconomic (country-level) factors, guiding countries seeking to achieve market success by developing smart organizations. The third study has a similar aim but with a more focused target, as the authors create a framework to achieve smart industries that are smart and effective, with case studies within the coffee industry in Indonesia.

3.1.5. Business and Commercial Sectors

Sustainable smart technologies are rapidly becoming an essential part of businesses worldwide, driven by the need for efficient and environmentally friendly practices in a highly consumerist generation. These technologies have the potential to revolutionize traditional business models, offering solutions that not only optimize operations but also mitigate environmental impacts, achieving sustainability. This category included 8 out of 32 studies.

As this field highly depends on productivity, many researchers have opted to conduct assessments and exploratory studies on this topic. These assessments involve different subtopics; however, a denominating factor is the aim of measuring the effects of smart technology integration within businesses to create an e-business. An example of this is the study by [31], where the authors propose a model that aims to predict the influence of IoT devices on businesses when combined with the IT knowledge of the users and have found positive results indicating that not only does smart technology have a positive influence on businesses but also that certain factors, such as the quality and security of the IoT services, dictate this influence. Conversely, another study in [32] assessed the influence that such technology has on the productivity of workers in the telecommunications sector, with results that strongly support the claims that integrating smart technology within a business has positive influences. Similarly, the study in [33] explores the effects of having a smart business environment on corporate investments and takes China’s Hangzou as a case study. The researchers found that integrating smart technology in businesses increases investments by enhancing business confidence and decreasing institutional costs.

Although most studies consider sustainability and smart technology from the perspective of companies and enterprises, some studies also consider the perspectives of end users and consumers. In the study of [34], researchers explore the reasons that drive consumers into using or not using a service’s mobile app as a part of that service’s smart technology integration into their structure. The research shows that certain factors influence a consumer’s intention to use a smart service or abstain from doing so, and the authors identify these issues for future researchers to use as a reference, as well as for enterprises to gain insights into the minds of consumers in the context of smart technology in services. Another significant study addresses consumer importance in reference [35]. The study focuses on how companies utilize their resources to add value for customers and enhance their profits and growth. The authors highlight the challenges entrepreneurs face when attempting to expand their markets. To tackle this issue, the study introduces a new approach called the Multimedia-assisted Business Evaluation Model (MBEM), which leverages machine learning to enhance companies’ efficiency.

There has also been some research that considers how businesses might use consumer data to enhance the sustainability of their business, and one such study was conducted in [36], which focused on how businesses utilize data analysis, particularly through social media analytics (SMA), as part of their decision-making processes. The authors noted that extracting meaningful business data can be challenging amidst the abundance of content on social media, and they proposed a business decision-making system (BDMS) that utilizes social media data analytics to inform business strategies. The experimental results demonstrate that the BDMS outperforms other methods regarding accuracy, system dependability, and measurement metrics such as the F-1 score.

Within the topic of businesses, some studies from the collected literature note that SMEs encounter challenges such as technology adoption, trust building, and managing big data when implementing I4.0 solutions. To address these challenges, ref. [37] propose several solutions, including guidelines and frameworks for SMEs to implement. The effectiveness of these solutions is evaluated using a case study involving a Greek SME, demonstrating their practical applicability and potential benefits for real-world implementation.

A more general approach to these topics can be found in [38], in which the authors aimed at understanding the evolution toward Industry 5.0, focusing on innovation, technology management in industry and business, and the defining characteristics of smart industry, business, and services in their study. The authors propose dividing production processes into standardization, adaptability, and predictability stages to facilitate consistent digital transformation, abandon outdated processes, restructure workflows, and foster new business cooperation.

3.1.6. Healthcare Sector

Integrating healthcare and information technology has taken many years, with new advancements propelling the sector forward continuously. As with previous sectors, when technology is included in a field, sustainability questions will soon arise at one point or another. This section discusses 2 out of 32 studies concerning the sustainability of smart technology within the healthcare sector.

Based on the collected literature, this topic still needs to be added in terms of related research. Both of these studies were mostly review-based and exploratory. The first study in [39] discusses the evolution of healthcare services toward more personalized and IoT-based solutions based on recent technological advancements such as the IoT and 5G and economic goals such as the UN 2030 Sustainable Development Goals. These services rely heavily on artificial intelligence (AI) and machine learning (ML) algorithms to enhance the efficiency of traditional healthcare systems. However, they often need to address the interconnected nature of various health conditions, leading to inaccurate diagnoses and impacting patient sustainability and long-term health. Therefore, the authors conducted a comprehensive survey on personalized healthcare services. A three-layer architecture for IoT-based healthcare systems is proposed, examining both AI and non-AI-based approaches and discussing their strengths and weaknesses in the context of personalized healthcare services.

Moreover, another study, [40], also emphasized the importance of connectivity and interoperability in information and communication technology (ICT) infrastructure when integrating with medical systems. The aim is to provide cost-effective, widespread, and timely healthcare services to those in need. The authors explore how IoT-based connectivity can lead to improved healthcare solutions, especially in recent implementations of IoT-based healthcare solutions. Additionally, the authors discuss future opportunities for leveraging IoT concepts to enhance healthcare solutions further.

3.2. Information System Types to Support Sustainability

Information system types to support sustainability refer to various information systems designed and implemented to contribute to sustainable practices in different domains. Sustainability generally refers to meeting the needs of the present without compromising the ability of future generations to meet their own needs. Information systems support sustainability efforts by providing tools, data, and analysis to help organizations and individuals make informed decisions considering environmental, social, and economic impacts [41]. This category consists of 6 subcategories among the 32 studies, as shown in Figure 3.

3.2.1. Transaction Processing System (TPS)

A Transaction Processing System (TPS) is an information system that manages and processes an organization’s day-to-day transactions in real-time, ensuring high efficiency, data accuracy, and reliability. It handles routine tasks such as sales, inventory updates, and financial transactions, providing immediate and up-to-date information for operational decision-making [42]. This category included 3 out of 32 studies.

Fraga and his colleagues [24] studied the automotive industry. This complex and technologically advanced sector has developed innovations such as hybrid, electric, and self-driving cars, in addition to IoT connectivity. Blockchain technology has been identified as a potential game changer that offers improved data security and transparency. This research explores blockchain’s application in addressing current challenges, emphasizing its cybersecurity features and relevant use cases. The widespread adoption of blockchain could reshape business models and disrupt car sharing. Recommendations are provided through a SWOT analysis for future cyber-resilient developments in the automotive transaction processing system industry [17]. The supply chain is vital for manufacturing and industry intelligence sustainability, with a focus on smart technologies. The smart supply chain, which utilizes tools like the Internet of Things (IoT), enhances quality and decision making. The IoT, a key component of IT infrastructure, generates significant amounts of big data, driving strategies for data analysis. This paper explores supply chain strategies, specifically in the fast-moving consumer goods (FMCG) industry, by proposing an analytical framework for a sustainable smart supply chain using IoT-based big data analytics. The emphasis is on IoT implementation methodology and expert reviews to improve the production decisions of a transaction system. In [34], the authors also focused on a transaction processing system in which mobile technologies drive courier services to adopt mobile applications, allowing customers to place orders and transactions online. This study in Indonesia focuses on factors influencing user intention for a state-owned enterprise’s courier services application. Factors, such as ease of use, service quality, price value, and attitude, significantly impact user intention.

3.2.2. Office Automation System (OAS)

An Office Automation System is an information system designed to streamline and automate routine office tasks such as document creation, communication, and data management. It enhances efficiency by integrating various office functions, improving collaboration, and supporting day-to-day operations in a workplace [43]. This category included 0 out of 32 studies. Less attention has been paid to using OAS in the context of sustainability.

3.2.3. Knowledge Work System (KWS)

A knowledge work system (KWS) is tailored to support knowledge workers in tasks involving information analysis, decision making, and problem solving. It aids in managing and processing complex data, facilitating collaboration, and enhancing the intellectual capabilities of individuals engaged in knowledge-intensive activities within an organization [44]. This category included 2 out of 32 studies. Although we managed to clarify 2 studies under the KWS, it is evident that more is needed to sustain KWS.

Ballina [17] explored smart tourism (ST), which requires evolving smart business practices. This research assesses the future outlook of smart components in tourism companies by exploring the perspectives and factors that drive their acceleration. Based on a survey of 133 managers, the focus is on the future development of information and communication technologies (ICTs) and smart tourism (ST) in knowledge work systems. Notably, research on smart business knowledge work tourism systems is limited compared to that on smart destinations and smart tourists, and managers from significant tourism companies support the findings. Moreover, in [35], Zhong and his team proposed that business model evaluation is critical for companies, balancing capital use for consumer value, income, and growth. Based on machine learning, the Multimedia-assisted Business Evaluation Model (MBEM) aims to enhance business efficiency. Multimedia’s rights protect commercial models in digital content distribution. The proposed DSSs based on machine learning improve organizational decision making. The experimental results show that the MBEM enhances business evaluation, decision making, performance, and profitability compared with other methods.

3.2.4. Management Information System (MIS)

A Management Information System (MIS) provides managers with the tools and data for effective decision-making and organizational control. It gathers, processes, and presents information from various sources to support business operations planning, analysis, and monitoring. MIS enhances managerial efficiency by delivering timely, relevant, and organized information critical for strategic and operational decisions [45]. This category included 10 out of 32 studies.

The study of [31] proposed a model affirming that the quality of IoT services (scalability, availability, reliability, and ease of use), security (trust, reputation, privacy, and encryption), and users’ IT knowledge (usage skills, awareness, experience, and accuracy) positively and significantly impact e-business and management information systems. Additionally, the results show that the operating cost of IoT services (transmission time, storage capacity, functionality, and stability) is significantly influenced by the development of e-businesses. Additionally, Arenas and his research fellows [15] showed that little prior research has explored how information technology contributes to developing a design-centered digital ecosystem. Using a capabilities lens, this study investigates the pathways through which IT facilitates the establishment of a design-centric smart tourism ecosystem as a management system. Based on archival data and interviews in Spain, a leader in smart destinations, the analysis reveals specific IT-enabled capabilities crucial for implementing smart tourism projects. Many available IT resources are vital in developing the capabilities to create a design-centric smart tourism ecosystem.

In [7], it was stated that smart cities utilize management information and communication technologies to enhance citizens’ quality of life, the local economy, transport, traffic management, the environment, and government interaction. This study concisely synthesizes the relevant literature, analyzing key findings on smart cities from an information systems perspective. The focus includes smart mobility, living, environment, citizens, government, architecture, and related technologies and concepts. The discussion also addresses the alignment of smart cities with UN sustainable development goals, offers critical insights into key research themes, highlights current limitations, and suggests potential future directions. Esmaeilian and his team [19] aimed to provide an overview of how blockchain technology and Industry 4.0 can advance supply chains toward sustainability. The evaluation begins by assessing Industry 4.0 capabilities for sustainability, focusing on IoT-enabled energy management, smart logistics and transportation, and smart business management models. Additionally, the study explores blockchain’s contributions to sustainability in incentive mechanisms, product lifecycle visibility, management system efficiency, and sustainability monitoring across supply chain networks. The discussion covers blockchain’s potential impact on social and environmental sustainability.

Taimoor and Rehman [39] explored the evolution of healthcare 5.0 technology, aiming for fully autonomous healthcare services considering the interdependent effects of various patient management methods. The focus is on personalized healthcare services within the Healthcare Internet of Things (HIoT) as a management system. The survey begins with an overview of the critical requirements for comprehensive, personalized healthcare services (CPHSs) and introduces a three-layered architecture for IoT-based healthcare systems. The strengths and weaknesses of AI and non-AI-based approaches for CPHS are discussed, and the paper also addresses security threats at each layer of the IoT architecture, proposing potential AI and non-AI-based solutions.

Zhu and Shang [46] address the need to enhance rural management tourism systems in the Internet era, aiming to modernize the tourism model. It introduces a rural smart tourism system, integrating the Internet plus technology to improve efficiency. The authors analyzed the application of Internet Plus in the smart tourism system architecture and presented a cloud service-based rural tourism data system. The architecture includes a cloud data center, a business management platform, and a tourist behavior intelligence analysis system. The paper concludes by analyzing the system’s performance through experiments, indicating the positive effects of the constructed rural innovative tourism system. In [29], the authors of the Industry 4.0 Revolution (IR) also presented opportunities and challenges for organizations to shape a modern smart world. Intelligent organizations, known as smart organizations IR 4.0, play a crucial role in adapting to technological advancements and promoting sustainable development. This research emphasizes the growing influence of smart organizations in shaping competitiveness and achieving sustainable development goals, especially in the European Union (EU). The focus is on identifying critical factors for smart organization development and proposing an effective tool to monitor their impact on building competitiveness and sustainable development in countries, particularly within the EU.

Fajrillah and his research team [30] focused on digital-based concepts aligned with technological developments. Implementing a smart management industry requires a well-defined IT strategy to ensure adequate investment. This study utilizes the Ward and Peppard framework, comprising internal and external business management system analysis, to design a systematic IS/IT strategy. The output includes IT management strategies, business information systems, and IT strategies, resulting in a portfolio of IT designs for the Margamulya Coffee Producers Cooperative, encompassing business and IT management strategies.

Nalajala and his research fellows [47] show that the Internet of Things (IoT) has revolutionized the manufacturing sector, offering advantages such as increased productivity, reduced expenses, and a more sustainable business and management model. This study is based on abductive qualitative research and case studies in the heavy-duty vehicle sector and explores the challenges and security issues related to manufacturing. This research emphasizes the role of the IoT in virtualizing manufacturing processes and ensuring seamless management of supply chain systems and operations by gathering real-time data. Furthermore, in [10] it was explained that smart technology, which spans various sectors, offers productivity benefits and performance improvements. While urban areas initially attracted more interest, recent studies have highlighted increasing opportunities and appeal in rural regions. Sustainable development in rural contexts relies on technological innovation, with smart city management systems and models being successful in urban settings. However, its practical application in rural areas under a sustainable development approach still needs to be defined. This study uses content analysis to explore the challenges and gaps in adopting smart city features in rural contexts, such as farming, education, business, healthcare, and governance.

3.2.5. Decision Support System (DSS)

A decision support system (DSS) is designed to assist decision makers in analyzing complex data and information to make informed and effective decisions. It provides data modeling, analysis, and visualization tools, helping users evaluate alternatives and solve unstructured problems. DSSs enhance decision-making processes by offering comprehensive insights and facilitating the exploration of various scenarios to support strategic and tactical choices [48]. This category included 1 out of 32 studies.

Yang and his team [36] focused on business intelligence, mainly social media analytics (SMA), which has become pivotal in decision making, leveraging data from social media platforms for in-depth insights into social consumers. This study proposes a business decision-making system (BDMS) focusing on marketing and operational approaches to extracting valuable information from social data. The BDMS aims to understand critical principles, issues, functionality, and developments in big social data. Despite social media’s content saturation, the BDMS ensures an accurate and dependable system with competitive results, achieving high measurement accuracy and low deviation rates. The experimental results demonstrate the effectiveness of BDMSs in decision support and investment opportunities. Notably, less attention has been given to the role of decision-making systems in sustainable development.

3.2.6. Executive Support System (ESS)

An executive support system (ESS) is an information system specifically crafted to meet the needs of top-level executives. It provides summarized, graphical, and easily accessible information from various sources, aiding executives in strategic decision making. ESS presents key performance indicators, trends, and critical data to support high-level management in understanding the organization’s overall performance and making informed choices for the future [49]. This category included 1 out of 32 studies.

Zeadally and his team [40] showed that connectivity and interoperability are crucial features in designing information and communication technology (ICT) infrastructure, especially for an executive support system. Integrating Internet of Things (IoT) technologies with medical systems enhances healthcare services and provides cost-effective and timely solutions. Leveraging the potential of the IoT for global device connectivity, this study explores and discusses how IoT-based connectivity can enhance the quality and delivery of the executive support system of healthcare services. It is also noteworthy that less attention has been given to the role of the executive support system in sustainable development.

3.3. Sustainable Development Components

The United Nations has designed 17 goals to achieve sustainable aspirations for a better future and sustainability in several ways [50]. These 17 goals address global challenges, such as poor status, environmental degradation, health, education, energy, economy, etc. When classifying these goals, we form three main groups that are considered pillars of the concept of sustainability. Social, Environmental, and Economic Sustainability. These pillars work in connection with one another to achieve sustainability. Although there is no single point of origin for these pillars, it seems “a gradual emergence from various critiques in the early academic literature of the economic status quo from both social and ecological perspectives on the one hand, and the quest to reconcile economic growth as a solution to social and ecological problems on the part of the United Nations on the other” [51].

In this section, while the intersection of sustainability with smart business is discussed, the pillars are designed from a slightly different perspective. Twenty-one studies were discussed that highlighted these pillars. Moreover, depending on the nature of sustainability and the intersection of its components, the majority of the reviewed papers underscore multiple facets of sustainability rather than focusing solely on one and are discussed in a section called the cross-cutting theme, reflecting a comprehensive examination of various sustainability components. Additionally, this section discusses how these studies align with the UN SDGs (see Figure 4).

3.3.1. Social Integration

The first pillar discussed is social integration. Smart business practices supported by these systems facilitate seamless communication with diverse stakeholders, fostering trust and community involvement. From embracing inclusive business practices to actively contributing to local community development, businesses become agents of positive social change. This section contains two studies discussing social integration.

In exploring the nexus of social integration within the domain of smart tourism ecosystems, the studies [15,17] shed light on the transformative role of information technology in public engagement and citizen centricity. The first study underscores the significance of public engagement capability in fostering collaboration and enhancing the relationship between citizens and government entities through ICT tools. By emphasizing citizen centricity, it advocates tailoring public services and resources to meet users’ diverse needs and preferences, and, thus, promoting a more inclusive approach to smart tourism design. Similarly, the second study delves into the importance of social capital and collaboration in crafting design-centric smart tourism destinations by providing personalized experiences and facilitating dialog between private and public tourism stakeholders.

3.3.2. Environmental Protection

Environmental protection is the second sustainability pillar discussed. Due to the escalation in the effects of climate change, we are witnessing almost the most essential pillar now. Integrated systems empower businesses to monitor and optimize resource usage, steering them toward sustainable consumption patterns. This section explores how businesses, through the integration of information systems, protect the environment. One study highlighted environmental protection directly as a main component.

The study in [22] emphasized using the Internet of Things (IoT) and big data analytics to develop a smart supply chain framework for fast-moving consumer goods (FMCG) companies. The framework aims to enhance the supply intelligence supply chain’s intelligence, particularly in terms of environmental sustainability. Various aspects of environmental sustainability are addressed, including monitoring and controlling energy consumption, reducing pollution, and eliminating inefficiencies in transportation.

3.3.3. Cross-Cutting Themes

Based on the nature and concept of sustainability achieved through the intersection of fundamental pillars, this section covers studies addressing the concept of continuity pillars and their intersection in several fields. Due to the vast majority of studies covering several aspects, this section contains 17 studies, most of which are included in this review. Here, studies interlace these dimensions, offering a comprehensive view of how technological advancements interact synergistically to achieve sustainability. While uniquely focused, each study contributes to understanding sustainability as an interconnected tapestry.

Researchers have strongly studied Industry 4.0, which plays a pivotal role in different aspects of sustainability. The studies examined in this review collectively present a comprehensive exploration of the intersection between Industry 4.0 (I4.0) technologies and sustainability across various sectors.

In [28], the intricate relationship between Industry 4.0 and sustainability was described by mapping thematic network structures to understand the impact of I4.0 technologies on the sustainability of different sectors. Building upon this foundation [26] conducts a systematic literature review on the similarities between Construction 4.0 and Industry 4.0, focusing on their direct impact on financial stability, social integration, and environmental protection throughout product/project life cycles. Subsequently, ref. [20] investigated how Industry 4.0 technologies in agriculture (I4TC) positively influence social, environmental, and economic performance, particularly in enhancing food production systems and supply chain coordination, aligning with UN Sustainable Development Goals. Finally, the researchers in [38] extended the conversation to include Industry 5.0, predicting it as a transformative paradigm emphasizing intelligent and sustainable technologies. The study emphasized the status of social integration along with financial considerations in shaping Industry 5.0 through digitalization, underlining the need for diverse, sustainable development. The above studies in this section provided valuable insights into leveraging Industry 4.0 and sustainability challenges across different industries.

The intersection of Industry 4.0 revolutions and blockchain technology provides convincing room for redefining sustainability. One study [19] investigated the impact of Industry 4.0 on sustainable supply chain systems, highlighting IoT-enabled energy management, green logistics, and transportation. Moreover, blockchain can be divided into four categories: incentivizing green behavior, enhancing product lifecycle visibility, increasing system efficiency, and improving corporate performance reporting. Other research, such as [25], has focused on decentralized marketplaces in developing countries, leveraging blockchain for supply chain traceability and transparency to promote sustainable production and support small-scale producers (SSPs). Additionally, ref. [52] investigated blockchain’s impact on the tourism sector, shedding light on its capacity to enhance sustainability through various applications. In [9], the focus was on converting cities into intelligent and sustainable cities by integrating the IoT and deep learning techniques. This initiative aims to optimize resource utilization in water waste management, electricity consumption, and transport traffic congestion, ultimately leading to favorable economic outcomes and a more practical living environment. The study of [47] examined the dual impact of IoT adoption in manufacturing, emphasizing financial stability and environmental protection. Additionally, ref. [29] underscores the potential for increased efficiency, cost reduction, and optimization of business models through IoT integration in manufacturing.

“Smart cities use an IS-centric approach to the intelligent use of ICT within an interactive infrastructure to provide advanced and innovative services to its citizens, impacting the quality of life and sustainable management of natural resources” is the definition of smart cities that depends on smart aspects developed by the authors of [7] with a focus on aligning smart cities with UN sustainable development goals. The study of [8] delves into the development of smart cities and industrial parks in China, showcasing a transition toward sustainability with a focus on environmental protection. The study discusses the evolution from pollution control to circular economy models and highlights the unique approach of Chinese smart city development.

The study of [16] concentrates on the sustainability of tourist destinations, stressing the importance of measuring progress over time and space and involving organized social agents in decision-making processes. Environmental protection and technological advancements are underscored as crucial elements within the sustainability framework, aligning with sustainability goals and addressing contemporary challenges such as climate change and waste management.

The researchers in [33] thoroughly explored the intersection of technology, governance, and sustainability. This finding underscores the critical role of smart governance frameworks in encouraging financial stability. This emphasis on governance aligns with the broader theme of leveraging technology, as seen in exploring IS/IT strategies within the Indonesian coffee sector [30] and adopting smart technology in rural areas [10]. Moreover, the concept of digital sustainability [27] further deepens this narrative by highlighting the transformative potential of green services and digital opportunities in fostering sustainable business practices. Exploring social media data analytics [36] offers a practical toolkit for businesses to navigate these complex landscapes by harnessing customer perceptions and preferences insights.

3.3.4. Alignment with UN SDGs

This section highlights the direct relation of the previous sections with the UN Sustainable Development Goals. Our findings on social integration align with SDG 11 (Sustainable Cities and Communities) by focusing on the transformative role of information technology in public participation and citizen engagement that contributes to making cities durable and sustainable. Additionally, aligned with SDG 10 (Reduced Inequalities) highlighting citizen centricity, it advocates tailoring public services and resources to meet users’ diverse needs by ensuring that all citizens have equitable access to resources.

Concerning the environmental protection section, the study discusses SDGs 12 (Responsible Consumption and Production) and 13 (Climate Action) by utilizing IoT, and it also discusses its application to develop a smart supply chain to reduce environmental impact and pollution through resource optimization.

For the cross-cutting themes section, studies identified multiple interlinked SDGs facilitated by various technologies involving Industry 4.0, IOT, Blockchain, supply chain, smart cities, etc. These goals include SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), SDG 16 (Peace, Justice, and Strong Institutions), and SDG 17 (Partnerships for the Goals).

3.4. Information System Technology Employed for Sustainability

The convergence of technology and sustainability has transformed businesses. With the emergence of smart business practices, advanced technologies have been leveraged to optimize the use of resources and enhance the overall sustainability of technologies. Another section highlights the studies that use other technologies to sustain smart businesses. It is worth remembering that the nature of technologies is complementary, and utilizing multiple technologies to achieve the desired goal is quite common. Some technologies may be mentioned in a different category due to their use in the study as a non-core technology (see Figure 5).

3.4.1. Blockchain

First, ref. [52] explored the application of blockchain characterized by its decentralized and tamper-resistant ledger system and introduced various benefits, such as process automation through smart contracts and the reduction in fraud in payment systems. Furthermore, ref. [24] highlights the significance of blockchain in bolstering cybersecurity measures. Blockchain offers improved data security, privacy, and accountability by ensuring tamper-proof data and fostering trust among stakeholders through consistent data structures.

The study of [25] proposed a blockchain-based marketplace that leverages smart contracts to provide traceability of goods and services, particularly those produced in developing countries. The study of [19] discussed the integration of blockchain with Industry 4.0 to improve information integration across supply chains toward sustainability.

These studies collectively demonstrate the diverse ways blockchain technology fosters sustainability across different sectors, from automotive and manufacturing to international trade and tourism.

3.4.2. Artificial Intelligence (AI)

This study [21] delves into the application of artificial intelligence (AI) in supply chain risk management for small–medium enterprises (SMEs), mainly focusing on its role in fostering sustainability. This study highlights several key findings: AI enables dynamic responses to volatile environments and aids in cost-effective decision-making for SMEs; it influences supply chain re-engineering capabilities and agility, which are crucial factors for sustainability.

3.4.3. Internet of Things (IoT)

Starting with IoT in business, the study [31] delves into the influence of the IoT on e-business development, emphasizing factors such as service quality, security, operating costs, and user IT knowledge. Furthermore, the IoT’s role in real-time monitoring, product development, and optimizing business models within manufacturing processes is highlighted by [47]. A framework based on IoT and big data were implemented in [22] to examine informative supply chain development strategies by investigating the supply chain in FMCG industries.

Moving on to the healthcare sector; to improve healthcare services and to be able to consider different interrelated health conditions, studies [40,41] explored how IoT technologies are leveraged to enhance the quality and delivery of healthcare services, thereby fostering sustainability by enabling global connectivity and facilitating efficient healthcare services such as early diagnosis and remote monitoring.

Moreover, both [7,8] primarily focuse on smart cities and integrating technologies such as the IoT, the cloud, and ICT. The emphasis should be placed on the IoT and smart technologies for urban development and sustainability. Referring to smart cities, ref. [9] discussed monitoring and intelligent energy management using the IoT and explored this using a deep extreme learning machine (DELM) to create a predictive model to predict a combined cycle power plant’s hourly full-load electrical output.

3.4.4. Industry 4.0

Within the realm of Industry 4.0, researchers have explored its application across diverse industries, with notable attention given to sectors such as agriculture and supply chain management [20]. These studies underscore the potential of Industry 4.0 technologies for optimizing agricultural supply chains, thus promoting efficiency and mitigating environmental impacts.

Moreover, scholars have conducted bibliometric performance and network analyses to elucidate the relationship between Industry 4.0 and sustainability [28]. Their findings reveal concerted efforts to enhance economic and environmental aspects by clustering related initiatives. The researchers in [23] examined the theoretical underpinnings of Industry 4.0 technologies and their implications for BMI within seaport operation. This exploration sets the groundwork for subsequent studies aiming to address small and medium-sized enterprises’ challenges by integrating Industry 4.0 technologies, data science, and relevant standards [37].

3.4.5. Data Analytics (DA)

Researchers from Jordan have tried to employ a quantitative approach involving 121 employees within Jordanian telecommunication organizations; they utilized SPSS software to meticulously examine the effects of e-business strategies on human capital productivity [32]. Moreover, insights derived from social media via data analytics were demonstrated to inform business decision-making processes, indirectly bolstering sustainability efforts by addressing customer preferences and concerns [36]. Finally, structural equation modeling (SEM) utilizing SmartPLS software proved indispensable in validating hypotheses regarding user attitudes toward a specific application, PosAja, thus emphasizing the pivotal role of data analytics in evaluating factors such as perceived ease of use, usefulness, service quality, and the impact of price value on user attitude [34].

3.4.6. Other

Several studies have explored integrating smart technologies to enhance sustainability in various domains. One study focused on utilizing information and communication technologies (ICTs) and smart destinations to revolutionize territorial planning and management, particularly in coastal areas [16]. Another noteworthy contribution comes from a study delved into smart tourism architecture, particularly emphasizing the role of cloud services and Internet plus technology [46]. This research proposed a cloud service-based architecture for rural tourism systems, highlighting the significance of cloud computing in optimizing resource allocation and enhancing visitor experiences in rural areas.

Furthermore, integrating smart governance, digital public services, and big-databased social credit systems has been identified as pivotal in fostering sustainable business practices [33]. In a related context, utilizing information technology service management (ITSM) principles and the Ward and Peppard framework has been instrumental in designing comprehensive IS/IT strategies for smart industries [30] by aligning IT requirements with organizational goals and emphasizing sustainability principles.

4. Bibliometric Analysis

The provided bibliometric analysis offers valuable insights into the research landscape, including the temporal scope, sources utilized, document characteristics, authorship patterns, and document types. This comprehensive information provides a foundation for further analysis and exploration.

Table 2. General information about the research articles.

MAIN INFORMATION ABOUT DATA
Timespan	2019:2024
Sources (Journals, Books, etc)	24
Documents	32
Annual Growth Rate %	−24.21
Document Average Age	2.5
Average citations per doc	61.34
References	0
DOCUMENT CONTENTS
Keywords Plus (ID)	311
Author’s Keywords (DE)	146
AUTHORS	119
Authors of single-authored docs	2
AUTHORS COLLABORATION
Single-authored docs	2
Co-Authors per Doc	3.75
International co-authorships %	46.68
DOCUMENT TYPES
article	29
review	3

illustrates the primary information. Table 2 shows some general information regarding the research article.

4.1. Annual Scientific Production

The annual production of research articles within the specified timeframe shows a fluctuating trend, with notable variations in output from year to year. In 2019, 2020, and 2021, four articles were consistently produced per year, indicating a stable level of research activity. However, there was a significant spike in 2022, with a remarkable increase to 13 articles, suggesting a period of heightened research productivity or a surge in interest in the field during that year. In 2023, only six articles were produced, suggesting a return to a more typical output level. In 2024 there was only one article, a significant decrease from the previous years. This fluctuating pattern shows how research output can change over time and how many factors can affect it.

Table 3. Annual scientific production.

Year	Articles
2019	4
2020	4
2021	4
2022	13
2023	6
2024	1

shows how much science is produced each year. The number of articles remained consistent from 2019 to 2021, with no noticeable growth at four articles each year. A significant increase of 225% occurred in 2022, rising to thirteen articles. However, this was followed by a 54% decline in 2023 to six articles, and a further 83% decrease in 2024, dropping to just 1 article. The data shows a peak in 2022

4.2. Country Scientific Production

The data on country scientific production show that different regions contribute differently worldwide. Spain has 15 scientific publications, which shows how strongly its research is progressing. After Spain, India has made 12 scientific contributions. Productions that focus on science and technology. Then, China comes in at third with 11 publications. This shows how quickly science is becoming better and how much money is being spent on it. The United States has nine productions, showing it is still a scientific leader with its expert scientists. The United Kingdom has contributed seven scientific publications, showing its strength—schools and research centers. Iran has five science projects, showing that it is becoming more critical. France, Pakistan, and Ukraine each have four working scientific projects. Participating in research in these countries. Italy has three scientific productions on its list. This paper shows that it is committed to contributing to global scientific knowledge. This information shows many things. Many people around the world are involved in science; some have made significant contributions.

Table 4. Country scientific production.

Region	Frequency
SPAIN	15
INDIA	12
CHINA	11
USA	9
UK	7
IRAN	5
FRANCE	4
PAKISTAN	4
UKRAINE	4
ITALY	3

below shows strong scientific nations and emerging research hubs.

However,

Table 5. Countries’ production over time.

Country	Year	Articles
CHINA	2019	3
CHINA	2020	3
CHINA	2021	4
CHINA	2022	11
CHINA	2023	11
CHINA	2024	11
INDIA	2019	1
INDIA	2020	1
INDIA	2021	1
INDIA	2022	6

below, which shows scientific production throughout time, demonstrates the remarkable growth of China and India in the scientific community. From 2019 to 2024, China presented a steady and substantial increase in scientific articles produced. Starting with three articles in 2019 and 2020, China’s scientific output grew to four in 2021 and then surged dramatically to eleven articles annually from 2022 to 2024. These numbers reflect China’s substantial research and rising prominence as a global leader in science and technology. However, the fact that India produces fewer articles than China does also explains the significant progress in its scientific production. From 2019 to 2021, India maintained a steady output of one article per year. However, in 2022, India’s scientific production significantly increased, with six articles published.

These data illustrate the dynamic growth in scientific production in both China and India, with China leading the way with a rapid and sustained increase in articles and India showing a marked improvement, particularly in recent years.

5. Conclusions and Future Work

This systematic literature review underscores the critical role of information systems in advancing sustainability initiatives, particularly within the framework of the United Nations’ 17 Sustainable Development Goals (SDGs). By integrating business intelligence and other technological innovations, such as Blockchain, the IoT, and Industry 4.0, various sectors including tourism, health, and urban development have made significant progress toward achieving sustainability objectives. The 32 high-quality studies were categorized into four main categories to provide a comprehensive understanding of the applications and impacts of information systems on sustainability practices in the context of the digital environment. This review highlights the potential of information systems to drive sustainable development by enhancing efficiency, transparency, and decision-making processes across different domains.

Our future research will focus on expanding the scope of this review by including more recent studies and exploring emerging technologies that can further enhance the intersection of information systems and sustainability. It would focus on secure information systems, investigating the long-term impacts of implementing these technologies on sustainability goals, and observing case studies from a broader range of sectors can provide deeper insights. There is a need to develop standardized metrics and frameworks to measure how effective information systems are at achieving specific SDGs. Working with academics, businesses, and government officials is essential to create new ideas and to ensure that new technology helps the world stay sustainable. Finally, addressing challenges related to data privacy, security, and ethical considerations will be necessary for advancing the integration of information systems for sustainable development.

Additionally, we aim to integrate artificial intelligence and machine learning into our topic to investigate how those technologies can optimize resource allocation, energy consumption, and waste management in sustainable practices. This could include projecting analytics for sustainability estimation and forecasting. How this research outcome will impact society will be further researched in the future also.