The Boundary Conditions of Information Sharing and Sustainability: The Mediating Role of Supply Chain Resilience

Abstract

Sustainability is a goal for modern organizations since every organization aims to be in operation for the number of years needed to achieve profitability and even diversify for continuous survival. To achieve sustainability, firms need to understand and adopt the triple bottom line of sustainability, which is the economy, the environment, and society. This research draws on information processing theory and uses complementary insights from stakeholder theory to examine the significance of information sharing in organizational operations towards the holistic achievement of organizational goals. Primary data was obtained from 236 companies out of 255 surveyed from four (4) regions in Ghana operating in five (5) industries, which were mining, extraction, manufacturing, distribution, and service provision. Statistical Package for Social Sciences (SPSS 25) and Mplus version 7.4 were used to conduct the analysis. The results revealed that information sharing is positively related to sustainability. Additionally, resilience partially positively mediates the relationship between information sharing and sustainability. However, the use of technological tools did not strengthen the positive relationship between information sharing and supply chain resilience. Similarly, entrepreneurial orientation did not moderate the positive relationship between supply chain resilience and sustainability. This study emphasizes the important role of supply chain resilience in explaining how sustainability can be achieved through the timely sharing of information. Furthermore, constant efforts by organizations to train employees to embrace the use of technological tools to enhance sustainability are highly recommended. It was concluded that managers can implement a range of policies for insightful actions geared towards collaboration and improved environmental/social/economic performance across supply chains.

1. Introduction

Firms around the world are integrating sustainable strategies into supply chain management. Research on sustainability has led to a sustainable supply chain, which is crucial in business today, mostly due to the growing interconnections of the world’s economies and people, which have given rise to international trade in services, materials, technology, investment, and information. This has prompted organizations to pursue a higher strategic level of management by pursuing innovation, continuous improvement, and strong supplier management to leverage the numerous advantages they bring and address associated risks to sustainability [1]. However, risks associated with globalization, including natural disasters and pandemics like COVID-19, the war between Russia and Ukraine, geopolitical risks (trade wars such as that between the USA and China, leading to tariff increases and government instability), differences in laws and regulations [2], and others, make organizations vulnerable and the consequences of possible interruption severe [3]. Hence, for an organization to avert these risks and achieve sustainability, the goals of the stated sustainability measurements (economic, environmental, and social) need to be established, and they are usually driven by stakeholder requirements and customer demand [4]. The merits of sustainability cannot be overemphasized since it drives the world economies to greater heights and has been the focus of the United Nations’ objectives through the Sustainable Development Goals (SDGs). The 2030 Agenda for Sustainable Development was adopted by all the United Nations Member States in 2015 with the aim of promoting peace and prosperity for the planet and its people now and in the future, giving an urgent call for action to be taken by all countries, both developing and developed, engaging in global businesses. As stated in the 9th of the 17 goals of Agenda 2030, “Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation”, organizations are urged to increase resource use by adopting environmentally sound technologies and processes based on their capacity to increase sustainability [5]. There are several drivers, both external (market pressures, societal pressures, and regulatory pressures) and internal (corporate strategy and organizational culture, resources, and characteristics), which have an influence on an organization’s supply chain. The level of influence of these drivers and the interdependence of organizations, in line with their complex supply chain networks, have enhanced both the level of vulnerability and the effects of a potential operational disruption [6]. Every organization aims to continue operations after a disruptive event and tries to avoid future similar events [7]. This has created the need for supply chain resilience strategies to be in place to curtail such occurrences.

In achieving a resilient supply chain and sustainability, partners depend primarily on the coordination of information sharing or flow [8]. Efficiency in the supply chain is crucial because today’s rivalry is not just between businesses, but also between supplier chains [9]. Organizations are searching for novel strategies to gain a competitive edge, including increased customer service and cost reduction. Adequate information flow within the supply chain network is a method to gain a competitive advantage [10,11]. The role information sharing plays in decision-making is vital when information technology (IT) is used, in the sense that organizations can dynamically reconfigure mutual processes in response to changing environmental requirements to increase sustainability. IT infrastructure can allow extensive information sharing and streamline disorganized upstream activities when integrated into higher inter-firm cooperation [12]. To achieve more transparent and efficient supply chains, collaborative IT investment among supply chain stakeholders has emerged as a strategic goal.

Incorporating sustainable practices into the supply chain helps organizations achieve independence in their processing [13]. However, to achieve greater innovation and gain a competitive advantage in today’s globalized economies, which is every organization’s aim, it is necessary to incorporate entrepreneurial orientation (EO), among other strategic approaches [14,15]. As proposed in [16], EO denotes an organization’s strategic posture in engaging in innovative activities, proactively venturing into new markets without allowing the risks to deter them from such opportunities. This is accomplished by acting entrepreneurially through competitive aggressiveness, innovativeness, proactiveness, autonomy, and risk-taking, putting the organization above its competitors. With the integration of EO and sustainable practices, organizations stand to gain power over their operational environment, both internal and external, to economically contribute to the world’s dynamic growth and improve their social performance towards understanding the complexities in the ecosystem [17].

Following the focus of this research, it is necessary to provide a review of the areas and variables used to improve understanding among researchers.

1.1. Supply Chain Management and Its Performance Drivers

As stated by [18], the concept of supply chain management has risen to prominence over the past decades, with most businesses mentioning this concept in meetings and conferences. The reasons for this popularity trend include global sourcing; healthy competition, primarily based on time and quality; and the stretch of the network of supply chain partners from upstream to downstream, which have contributed to this trend [19]. A supply chain has five major drivers that influence its performance positively and can reduce its performance if not managed adequately. These drivers are production, inventory, location, transportation, and information. When managed effectively, these drivers can achieve the optimal balance between efficiency and responsiveness [20]. Though all these drivers play significant roles in the performance of supply chain activities, this study limits its review to information due to its function as the coordinator of the other drivers and its alignment in a supply chain towards achieving a competitive advantage. Information sharing coordinates the other drivers by increasing efficiency by optimizing inventory, smoothing production, improving visibility in the supply chain, and enhancing agility and collaboration [21].

1.2. Etymology of Information Sharing and Its Links to Resilience and Sustainability

Supply chain management (SCM) theory suggests that sustaining competition and long-term relationships, leading to organizational performance, requires close coordination among its partners [22]. The authors of [18] affirmed that the fundamental function of the SC is timely information sharing. Information sharing is the glue that holds the supply chain together regarding partnership coordination. However, miscommunication can happen if the correct information is not shared, creating possible conflicts among partners and defeating the purpose of achieving superior performance [23,24]. Information sharing cannot be achieved holistically without its influence on sustainability, resilience, agility, visibility, coordination, and other SC performance indicators. Researchers and managers frequently cite information sharing as a key factor that facilitates cost reduction. Still, its value in a sustainable supply chain has received limited attention in the literature, as opined in [25]. Nevertheless, the impact of information sharing on the performance of the SC has been significantly studied in the recent literature. Regarding resilience factors, information sharing strategies can weaken the effect of disruptions and were also affirmed to play a role in the relationship between supply chain members by coordinating their activities [26].

1.3. Sustainable Supply Chain

The interest of academia and corporations in sustainable supply chain management (SSCM) has gained massive ground in the past decades. Several papers have been and are still being written to articulate the essence of this business field [27]. This trend of increased interest is necessitated by the interdependence of organizations, making current business competition at the level of supply chains more important than any other variable [28]. Marchese et al. also argue that the current trend in interest is due to the concerns of businesses and individuals about the environment, the economy, and society [29]. The operationalization of sustainability is made possible by accepting the triple bottom line, where environmental, cultural, and economic performance is expected [30]. Hence, the authors of [31] defined SSCM as an integrated system of thinking, strategy, and action in supply chain management, including financial, ecological, and social performance.

1.4. SDG Agenda of the United Nations on Sustainability

The United Nations (UN) is an intergovernmental organization aiming to uphold global peace and security, foster goodwill among states, promote international collaboration, and operate as a hub for coordinating national policies. In 2015, the UN adopted 17 Sustainable Development Goals, which seek to advance institutional integration and policy consistency among the numerous international organizations [32]. The outcome of these goals evolved into an agenda, termed the 2030 Agenda for Sustainable Development. The 2030 Agenda for Sustainable Development Goals (SDGs) targets integrating sustainable development into all aspects of life, tackling formulation, operational implementation, and administrative processes, making member countries dedicate considerable amounts of money to achieving the SDG agenda [13]. The ninth point under the 2030 Agenda for Sustainable Development Goals (SDGs), often called SDG 9, is to offer “Industry, Innovation, and Infrastructure.” The main aim of SDG 9 is to build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation by harnessing innovations towards finding solutions to increase economic growth and societal benefits while decreasing adverse environmental impacts [33]. This study aims to contribute to achieving this 9th goal of the 2030 Agenda.

1.5. Resilience and Sustainability

Analysis of the relationship between resilience and sustainability has been supported by the supply chain management theory since the sustainability of a supply chain is a measure of how resilient it is [20]. The relationship between resilience and sustainability indicates that it can be in three dimensions: sustainability and resilience as separate conceptual objectives, sustainability as a constituent of resilience, and resilience as a constituent of sustainability. Among the above dimensions, the article established the third one as a major contributor to organizational performance since it analyzes resilience as a prerequisite condition essential for accomplishing sustainability. The concept of sustainability and resilience exemplifies complex systematic issues that need a cooperative implementation plan from the focal firm towards achieving one goal and decreasing underperformance, which can happen due to their similarities [29].

1.6. Technological Tool Usage

Technological tool usage, the application of technology to process, store, transmit, and retrieve information within an organization or for personal use, has gained a central role in today’s business, making it very difficult for a firm without any IT tool usage to be competitive [34]. Information technology is essential to supply chain management, as it enables businesses to communicate with their supply chain partners in this dynamic and complex business environment. Suppliers are adequately coordinated through IT tools, allowing inter-firm harmonization and enhancement of Business-to-Business (B2B) communication from the electronic point of sale, the web, and others. Information technology encompasses a wide range of tools, systems, and applications that facilitate the management and communication of information. Digitalization remains the process by which a company, sector, nation, etc., adopts or uses digital or computer technology more frequently to facilitate its organizational operations [35], which can be structured around diverse domains of communication and media [36].

1.7. Entrepreneurial Orientation

One of the strategic efforts used by organizations to exploit and understand the dynamics of today’s business environment is entrepreneurial orientation (EO). An organization’s capacity to take measured risks, adopt proactive measures, and hunt for innovation is a crucial strategic endeavor to attain improved performance in the face of ever-evolving customer demands and technologies, as proposed in [15]. EO is a process that characterizes an entrepreneur’s behavior towards engaging in a new business venture. In line with this, EO entreats businesses to react to environmental disruptions by seeking new opportunities and providing innovative solutions that set their business apart from rivals in the market [37]. Further research shows that a firm’s EO denotes whether the firm’s strategic posture is innovative enough to embrace a new changing environment and proactively envisage and seek future opportunities while standing in a position to accept and mitigate any risks that will come [38]. EO has five operational dimensions: innovativeness, proactiveness, competitive aggressiveness, autonomy, and risk-taking. This research aims to determine EO’s role in achieving resilience and sustainability relationships.

1.8. Empirical Review

Several reviews and results have been published in the literature about information sharing, supply chain resilience, IT tool usage in enhancing operations, and sustainability. The level of correlation between sustainable practices and SC management in different organizations was examined in [39], where the findings stated that implementing sustainability strategies positively impacts novel linkages among partners. The authors of [1] conducted a systematic review of 1559 drivers of sustainable supply chains from 217 publications, which can influence organizations to undertake and implement initiatives. Recent research outlined a sustainable supply chain implementation process model based on a case study of an organization aspiring to become a global leader using a sustainable plan and the organizational learning literature [31]. Some other reviewed articles [40,41] provide outcomes on resilience and supply chain disruption to develop a conceptual framework for improving this business strategy.

Previous research [21] dealt with information sharing playing a significant role in building agility, visibility, and collaborations, among others, allowing managers to concentrate on significant achievements. However, they lack longitudinal assessment of data analysis to ascertain the correct determination of the influence of information sharing in this changing world of information technology. Using IT tools in this globalized economy enhances the achievement of business objectives [5]. An empirical review of different IT tools by [12,42,43] concerning exploitative and explorative patterns was conducted, concluding that supplier and customer resilience improve supply chains. The author of [44] concluded that there can be a positive relationship between entrepreneurial orientation and sustainability, even though the former is a company’s culture or way of dealing with its operations, whereas the latter is a set of postulates and objectives for implementation by a company. A recent study [45] looked at firm performance’s financial and commercial dimensions about entrepreneurial orientation and other variables.

2. Materials and Methods

2.1. Materials

2.1.1. Conceptual Model, Theoretical Lens, and Research Hypotheses

The study model outlines a positive relationship between information sharing and sustainability. Information sharing, the central pillar and a key driver of supply chain management and the foundation for decision-making, influences sustainability. In addition, to explain this relationship better, there is a need for a mechanism, which is resilience, because the more resilient an organization’s supply chain is, the more sustainable it becomes. It is necessary to introduce a moderator to strengthen the relationship between the independent variable and the mediator and give it proper direction; this moderator is technological tool usage (digitalization). Moreover, the relationship between the mediator “resilience” and the dependent variable “sustainability” could be explained better with the introduction of a moderator, which is entrepreneurial orientation (Figure 1). In-depth use of theories can be identified in various articles on achieving sustainable supply chain management. To examine the existing relationship between the variables, the study employs stakeholder theory with a complementary insight from information processing theory (IPT).

2.1.2. Research Theoretical Explanation and Research Hypotheses

Several theories have been propounded in supply chain management to provide conceptual understanding of factors that influence relationships, including Resource-Based View (RBV), transactional cost theory, stakeholder theory, knowledge base view, agency theory, strategic choice theory, institutional theory, information processing theory, and others. Dynamic capability theory was also applied by the authors of [10] to make their study on resilience more applicable due to the focus of this theory on rapid development and changing market environments. In the aspect of information sharing and information technology, many theories have been applied, such as information processing theory, transaction cost theory, and institutional theory, among others [12], which were based on numerous arguments, including IT tool usage enhancement in the flow of information in the focal firm and its partners. In the area of entrepreneurial orientation, major theories, including innovation theory, measurement theory, and need for achievement theory, have been explained and applied in published data [46]. It is notable from this viewpoint that it is impossible for a single theory to show or capture different aspects of the activities of a firm’s operations [47].

To examine the existing relationships between information sharing and sustainability and between information sharing and resilience, along with the interaction of technological tool usage and entrepreneurial orientation, the study employs stakeholder theory with a complementary insight from information processing theory (IPT). These theories suggest that a firm that wishes to achieve a conducive environment and has a highly competitive advantage needs to consider the opinions and expectations of its stakeholders toward sustainability [48]. The study hypothesized that

H1. 

Information sharing is positively related to a sustainable supply chain.

H2. 

Resilience mediates the relationship between information sharing and sustainability.

H3. 

Information technology (IT) tool usage moderates the relationship between information sharing and resilient supply chain.

H4. 

Entrepreneurial orientation (EO) moderates the relationship between resilience and supply chain sustainability.

The dimension of sustainability, which ensures that firms are sustainable by incorporating the environment, society, and the economy into their activities, is paramount to business development, as pointed out in [2], making stakeholders strategically present. Seeking to integrate environmental, social, and economic practices into the supply chain, firms demand unlimited access to information from their partners. Despite the force driving firms to address ecological, social, and financial issues and the frequently increasing demand for information sharing, companies still have little knowledge concerning the sustainability dimension’s impact on the production network. This calls for proper data, support tools for decision-making, and necessary incentives to pursue sustainable practices in SCM. The efficient sharing of information in the supply chain network allows businesses to achieve sustainability because stakeholders who are facilitators of this agenda for companies are highly involved. A complementary influence of information processing theory (IPT) affirms that the timely delivery of information to the right sector or person increases business growth. The primary focus of IPT includes the flow of information, individual input of data, record keeping, and storage and retrieval of information for organizational operations [49]. Similarly, the use of existing IT tools in firms and their partners shows how the organization pursues resilience activities.

IPT, in theory, sees a company as an open information processing system primarily made to deal with uncertainty [35]. The frameworks or capacities companies have to meet their information processing needs are the focus of information processing theory (IPT). Additionally, it examines how information consumption and organizational resources, like information, are related. As stated by IPT, the growth of firms is systematic and free from unpredictable internal and external processes. Nevertheless, this theory describes ideas of information processing and organizational behavior with a firm foundation [36]. The contribution of IPT makes supply chains work smarter by implementing and using new digital technologies like the Internet of Things (IoT), artificial intelligence (AI), and digital twins, among others, to study more operational areas, as mentioned by [37].

The theory states that information sharing cannot be achieved holistically without sharing with the appropriate supply chain sector [24]. A disrupted supply chain due to unfavorable conditions, including natural disasters, governmental and political insecurities, and pandemics, among others, can result in a flop in the performance of an organization [50]. This low performance by firms can be resolved by implementing tested strategies like resilience [5]. In this era of advanced globalization, IT-specific tool usage plays a significant role in gaining and maintaining supply chain resilience. The stakeholder theory trajectory of “development of resources and capabilities,” which is based on the co-creation of value, indicates that achievement of equal benefit and coordination among all partners is more important than profit maximization by the focal firm [51]. The digitalization of activities, which is a key success factor for redesigning the model of the SC, makes cloud-based strategies like the integration of the Internet of Things (IoT) and artificial intelligence (AI) important for overcoming disruptions in the firm and cost reduction. It is therefore essential to articulate that IT tool usage enhances the relationship between information sharing and resilience, since IT tool usage is the mode of transmitting the needed information. The active role of stakeholders in achieving sustainability also implies that, for an organization to be fully resilient and work towards sustainability, it needs innovativeness and proactiveness, among other necessary business strategies.

It is evident that the magnitude of disruptions organizations encounter puts pressure on organizational resources and capabilities in both the short and long term [52]. This confirms previous research findings that firm-level resources and capabilities add to supply chain resilience [37]. Successful dynamic organizations are constantly identifying new modern methods and ways of gaining a competitive advantage through novel services and production practices, and the entrepreneurial orientation (EO) concept has been developed from these continuous improvement ideas. This is so because EO brings innovativeness, proactiveness, risk-taking, autonomy, and competitive aggression into the business environment, contributing to organizational growth [36]. EO is a corporate strategy that enables businesses to respond to disruptive disturbances and uncertainties by providing a platform that facilitates the allocation of resources needed for long-term investment in business growth and sustainability [53]. The decision-making process of organizations, which comes from the interaction between stakeholders and firms, is crucial concerning resource utilization and competence in sustainable SCM. Resource utilization is important in both shareholder and Resource-Based View (RBV) theories in the three trajectories [51]. Regarding stakeholder theory, EO can be viewed as a resource supporting the achievement of a competitive advantage through innovation, proactiveness, risk-taking, and other dimensions [45]. Furthermore, information processing theory views firms as open information processing mechanisms dealing with numerous sources of uncertainties and changes but limiting the adverse effects’ impact through adequate information sharing [8].

It should be noted that the moderating role of EO in the relationship between resilience and sustainability has received minimal attention in the literature, a gap that this research seeks to bridge. Previous research has based its arguments on strategies like absorptive capacity, service-dominant logic, visibility, agility, and collaboration. However, we define EO as the strategic posture of an organization that is entrepreneurial and that engages more in innovation, risk-taking ventures, and proactive ventures, “beating competitors to the punch.” Therefore, this study argues that, for an organization to be sustainable, there is a need to understand the contribution of EO to achieving new goals. The effect of resilience on sustainability will be further enhanced when innovativeness reflects the organization’s ability to pursue, support, and develop new and creative ideas through existing resources or technologies. The proactiveness of the organization enables it to have a future orientation towards seizing new opportunities in the business environment. Risk-taking represents the willingness of the organization to commit resources to mitigating unforeseen risks or making investments. Autonomy and competitive aggression represent the independent actions of leaders toward success and the company’s adoption of decisive action to outperform its competitors [44].

As stated by several authors in the supply chain field, resilient supply chains have allowed several firms to envisage operational uncertainties that might affect them. Resilience allows the organization to plan proactively through the design of a supply chain network for the anticipation of disruptions or adverse events while maintaining control, which will invariably transcend to post-event robustness of the operation, thereby obtaining a competitive advantage. In addition, this ensures a cooperative posture for all shareholders toward achieving a common goal and considering all interests, beyond financial gain, in environmental, social, ethical, and economic domains [54,55]. Consequently, supply networks need to consider sustainability when managing resilience. They aim to create effective strategies to eliminate vulnerability and lessen the impact of potential disruptions, keeping in mind the supply chain’s long-term economic, social, and environmental components [56]. Sharing information, a driver for supply chain operations, cannot overemphasize the achievement of sustainability through the understanding of stakeholder theory. The four research hypotheses will be tested for their reliability and validity.

2.2. Methods

The main objective of this study is to develop a theoretical understanding of how information sharing influences sustainability and its managerial implications. The target population was senior managers from the mining, extraction, manufacturing, distribution, and service industries of selected regions in Ghana. These industries were chosen because they aligned with the study’s focus on information sharing and sustainability. These industries engage in global businesses that constantly search for resilient strategies to be competitive. Similarly, from a theoretical viewpoint, these industries have a strong foundation in facing sustainable pressures and are stakeholder-sensitive. Senior managers, due to their greater knowledge of the organization, experience, and expertise, have access to key information, among other resources. The authors in [57] state that, although the recommended minimum sample numbers for stable Maximum Likelihood Estimation solutions are 100 to 150, it has been found that a sample size as small as 50 can yield appropriate results. They continue to affirm that although the above statement is true, a sample size of 200 or above is an appropriate starting point for assessment. Researchers select participants from a favorable demography to obtain a sample to represent the population. The most effective method for obtaining a representative sample is to use probability (random) sampling procedures, which provide every member of the population with an equal chance of being included in the study with a determinable probability of selection. The assumption is that a random sample of the target population has been taken on the basis of traditional statistical inference tests. It is therefore advisable to select a sample size within the range from 200 to 400, depending on the study area. In total, 255 questionnaires were sent, and a total of 236 responses were obtained from the target population. This provided a fair representation of the population and was consistent with previous studies. The research adopted convenience sampling techniques to obtain responses due to the geographical location of the respondents, which was challenging to the researcher, but this sampling technique helped in overcoming the challenge. This was because the respondents were recruited from across the country to have a better representation of the companies in the country, and assessing these companies became easy with the use of this sampling technique. Additionally, target groups were specifically identified to ensure the research had diverse views from different industries, which this technique facilitated.

This study used a closed-ended questionnaire to gather its primary data from a field survey. These questionnaires were adopted from previously published data in the field of study and have been analyzed by scholars using the items obtained to measure comparable constructs. The data collection instrument adopted and used can be seen in Appendix B. In addition, insight from existing data in this study area was obtained from a secondary data collection, where a systematic literature review was conducted. Ethical approval is not necessary for this study because there is no possibility of harm arising from the conduct of the research. Informed consent was obtained from each participant in the research (Appendix A).

2.2.1. Validity and Reliability

Validity and reliability in research design are very crucial in any study since they ascertain the quality and accuracy of the data obtained. The degree to which a study accurately reflects or evaluates a particular concept that the researcher is trying to test is referred to as validity in research. However, the accuracy of the actual measurement device or process is what reliability refers to [39]. According to [40], the coefficients of variables are calculated to show the level of reliability in the data; thus, a coefficient of 0.8 or above indicates a high level of reliability. This study employed face validity through expert scrutiny to ensure that the instruments put in place in the questionnaires could adequately measure the variables of interest. The instruments in the study were designed to correspond to the appropriate questions. Internal consistency was ascertained using Cronbach’s alpha in SPSS 25 to ensure the suitability of the data. In addition, to validate the outcomes, proper measures were put in place to ensure that the results were reliable and therefore validated. Five pilot questionnaires were administered to experts and respondents in the field to determine potential inefficiencies in the instruments before final administration to the sample area. This pilot questionnaire helped the researchers to reshape the questionnaire to suit the intended objectives; the responses obtained were used to make corrections through probing the respondents and making the necessary changes to it. Valid research has the tendency to produce replicable results when given a similar sample, leading to interpretations with a different population, and reliability measures the accuracy of the data collection instruments [41]; this study met both criteria.

2.2.2. Data Analysis

According to [58], analysis of data is the organizing, structuring, examining, and modeling of data in order to find relevant information, make inferences, and aid in decision-making. This study employed both inferential and descriptive statistics for the analysis. MPLUS version 7.4 was used to perform the CFA and create the structural model.

2.2.3. Measurements of Variables

Key variables in the study were sustainability (environmental, social, and economic), information sharing, resilience, and entrepreneurial orientation—innovation, proactiveness, risk-taking, autonomy, and competitive aggressiveness. On the other hand, the study used technological tool usage to measure digitalization. A closed-ended questionnaire with a 7-point Likert scale was utilized. Respondents were given a scale that indicated how much they agreed or disagreed with the questions about the various constructs. One on the scale indicated extreme disagreement; two, disagreement; three, slight disagreement; four, neutral; five, slight agreement; six, agreement; and seven, firm agreement.

3. Results

The data presented here are all primary data gathered from the targeted sample already described, and Mplus 7.4 was used for further analysis.

3.1. Assessment of Measures

The study’s univariate and multivariate normality assumption was tested through the indicators put in place to check the distribution [59]. Non-normality was confirmed not to be a significant issue, as proven by the statistics attained in the ranges of the highest skewness (0.87) and kurtosis (1.33) observed in [60]. It is noted that most of the study’s indicators were taken from previous research works, and there was a need to use exploratory factor analysis (EFA) to understand the underlying structure and unidimensionality of the data [57]. Exploratory factor analyses (EFAs) of every multi-item indicator were performed using the main component and varimax processes for factor extraction and rotation. The data showed a Kaiser–Meyer–Olkin (KMO) index of 0.881, and Bartlett’s test of sphericity indicated statistical significance (χ² = 6458.805; df = 630), demonstrating that sample size and other factors were not a problem for the study. Therefore, eleven components were able to explain 81.26% of the variance in the data set. The percentage of variance explained ranged between 29.9% and 2.32%, while eigenvalues were between 10 and 0.89. Each result is over 0.72, showing that the threshold of 0.70 was reached. This further indicates that each collection of indicators has strong internal consistency according to Cronbach’s alpha (α), a measure of dependability. Descriptive and exploratory factor analyses are represented in Appendix B.

3.2. Common Method Bias (CMB) Assessment

The method of data collection used in this study has the potential to introduce bias. Thus, it was critical to assess standard method bias (CMB) and the degree of its threat to the study’s quality. When loaded on one construct, the EFA figures explained 29.735 percent of the variance, which is less than 50%, meaning one component could not explain more than 50% of the variation in the data set. Standard method bias was insignificant for this research. This is shown in

Table 1. CFA results—details of measures and validity test results.

Construct/Item Code	Measurement Items	Standardized Loadings	t-Values
Environmental Sustainability: CR = 0.861; AVE = 0.674; CA = 0.858
EnvSus3	We act towards the reduction of waste as a business improvement strategy	0.852	Fixed
EnvSus4	We substitute harmful and hazardous materials/parts, and services	0.846	14.628
EnvSus5	We support the Sustainable Development Goals (SDGs) agenda on the environment	0.761	12.718
Social Sustainability: CR = 0.825; AVE = 0.703; CA = 0.823
SocSus2	We apply fair employment practices to the local community	0.854	Fixed
SocSus4	We ensure timely and lawful payment of taxes and other obligations towards the state	0.822	10.972
Economic Sustainability: CR = 0.838; AVE = 0.639; CA = 0.822
EcoSus1	We believe that the achievement of returns on investment is necessary to survive business operations	0.739	Fixed
EcoSus4	We target producing at a low cost	0.96	10.812
EcoSus5	We support the Sustainable Development Goals (SDG’s) agenda on the economy	0.671	10.299
Supply Chain Resilience: CR = 0.933; AVE = 0.738; CA = 0.932
SCRES1	We are able to cope adequately with unexpected disruption in our supply chain by swiftly restoring its product flow	0.782	Fixed
SCRES2	We are able to adjust to our supply chain disruptions easily	0.815	14.024
SCRES3	We are able to maintain high situational awareness at all times	0.865	14.927
SCRES4	We are able to return to our original state of operations after been disrupted	0.936	16.592
SCRES5	We are able to move our operations to a new desire state after being disrupted	0.889	15.587
Information Sharing: CR = 0.910; AVE = 0.669; CA = 0.908
INFOSH2	Our supply chain partners and organisation are informed about events and changes that might affect each other through sharing of information.	0.761	Fixed
INFOSH3	We share timely information with our supply chain partners.	0.854	13.961
INFOSH4	We communicate among our supply chain partners frequently through available mediums (phone calls, emails, WhatsApp, face-to-face)	0.805	12.727
INFOSH5	We have adequate abilities to share standardised and customised information internally and externally.	0.862	13.568
INFOSH6	Complete information is shared among our supply chain partners and the organisation	0.802	12.571
Information Technology Usage: CR = 0.932; AVE = 0.773; CA = 0.930
ITUS1	We can coordinate the activities of our supply chain partners due to using IT Tools.	0.863	Fixed
ITUS2	We engage in electronic mailing capabilities with our supply chain partners by using specified IT Tools.	0.911	19.71
ITUS3	Our organization uses IT Tools to enable transaction processing with supply chain partners.	0.881	18.081
ITUS4	We obtain real-time information through our specified IT tool usage.	0.861	17.316
Entrepreneurial Orientation–Innovation: CR = 0.961; AVE = 0.891; CA = 0.960
EOINOV1	Our organisation supports innovative new products/services	0.909	Fixed
EOINOV2	Our organisation provides technological leadership in developing new products/services (including new and improved ways of operations)	0.972	28.514
EOINOV3	Our organisation has a long-term commitment to the development of R&D and continues to improve	0.949	26.338
Entrepreneurial Orientation–Pro-activeness: CR = 0.794; AVE = 0.564; CA = 0.790
EOPROC1	Our organisation searches and exploits anticipated changes in future business operations	0.81	Fixed
EOPROC2	We strive to take initiative continuously in every situation (e.g., a project, against a competitor)	0.722	10.379
EOPROC3	Seeking new opportunities in our business environment to make our business flourish is one of our objectives	0.717	9.619
Entrepreneurial Orientation–Risk taking: CR = 0.831; AVE = 0.624; CA = 0.819
EORT1	Our organisation shows concerns about tolerating dangers in venturing into new markets	0.732	Fixed
EORT2	Our business strategy supports committing resources to projects with uncertain outcomes	0.905	12.26
EORT3	Failures in new opportunities and ventures available to our organization do not deter us.	0.72	10.313
Entrepreneurial Orientation–Autonomy: CR = 0.904; AVE = 0.759; CA = 0.900
EOAUT1	Our organisation encourages employees to pursue business opportunities within the business environment for self-development (e.g., initiating ideas for continuous improvement)	0.817	Fixed
EOAUT2	Our organization supports the effort of employees that work autonomously	0.926	16.895
EOAUT3	Our organization believe that best results are obtained when employees decide for themselves the type of business opportunity to pursue	0.867	15.657
Entrepreneurial Orientation–Competitive Advantage: CR = 0.837; AVE = 0.721; CA = 0.834			Fixed
EOCA2	We adopt an “outperform-the-competitor” response in our business environment	0.886	Fixed
EOCA3	We take the lead to initiate action and strategies before our competitor	0.81	11.339
Chi-square/df = 827.487/539 = 1.535; RMSEA = 0.048 CFI = 0.954 TLI = 0.946; SRMR = 0.042

Source: Authors’ calculations.

.

3.3. Validity Measure

MPLUS version 7.4 was used to perform confirmatory factor analysis (CFA) utilizing the maximum likelihood estimate approach. Cronbach’s alpha was employed to assess the reliability of the metrics. The test results, which are shown in

Table A1. Descriptive and exploratory factor analysis.

Construct/Item Code	Item Descriptive Statistics				Exploratory Factor Analysis
	M	SD	Skw	Kut	Component Loading											Eigen value	%Variance Explained	α
					1	2	3	4	5	6	7	8	9	10	11
Environmental sustainability																1.628	4.524	0.858
EnvSus3	4.96	1.51	−0.51	−0.40	0.199	0.130	0.081	0.342	0.021	0.777	−0.025	0.050	0.034	0.065	−0.016
EnvSus4	4.70	1.68	−0.40	−0.72	0.158	0.127	0.116	0.228	0.013	0.816	−0.069	0.084	−0.002	0.121	0.079
EnvSus5	5.13	1.60	−0.77	0.05	0.064	0.134	0.133	0.204	0.148	0.799	0.044	0.057	0.002	0.131	0.081
Social sustainability																0.890	2.472	0.832
SocSus2	5.20	1.43	−0.80	0.35	0.138	0.101	0.203	0.320	0.104	0.138	0.063	0.123	0.068	0.769	−0.032
SocSus4	4.92	1.57	−0.64	−0.07	0.103	0.125	0.170	0.219	0.118	0.205	0.069	0.079	0.020	0.811	0.090
Economic sustainability																1.408	3.912	0.822
EcoSus1	5.08	1.56	−0.87	0.22	−0.085	0.080	−0.004	0.063	0.080	−0.064	0.857	0.019	0.013	−0.051	0.017
EcoSus4	5.28	1.41	−1.1	1.17	0.033	0.057	0.028	0.007	0.008	−0.039	0.915	−0.007	0.066	0.053	0.052
EcoSus5	5.54	1.30	−1.1	1.33	0.098	−0.067	0.095	−0.167	−0.003	0.072	0.802	−0.02	−0.066	0.102	−0.097
Supply chain resilience																10.705	29.735	0.932
SCRES1	5.30	1.46	−0.74	0.05	0.669	0.148	0.131	0.247	0.152	0.100	0.063	−0.02	0.199	0.020	0.328
SCRES2	5.08	1.57	−0.52	−0.46	0.752	0.268	0.166	0.122	0.200	0.084	−0.024	−0.11	0.106	0.079	0.105
SCRES3	5.19	1.66	−0.86	0.08	0.863	0.221	0.067	0.023	0.152	0.078	−0.013	0.048	0.083	0.124	0.056
SCRES4	5.33	1.55	−0.83	0.07	0.839	0.230	0.134	0.106	0.172	0.104	0.030	0.052	0.128	0.027	0.161
SCRES5	5.26	1.59	−0.87	0.04	0.794	0.210	0.122	0.128	0.187	0.174	0.028	0.025	0.114	0.058	0.153
Information sharing																4.525	12.568	0.908
INFOSH2	5.31	1.23	−0.58	0.34	0.328	0.743	0.027	0.129	0.052	0.195	0.002	0.046	0.089	−0.182	−0.017
INFOSH3	5.28	1.24	−0.58	0.35	0.192	0.824	0.009	0.072	0.167	0.072	−0.002	−0.01	0.187	−0.037	0.139
INFOSH4	5.37	1.19	−0.54	0.15	0.145	0.818	0.109	−0.012	0.173	0.019	0.026	−0.01	0.070	0.072	0.002
INFOSH5	5.43	1.17	−0.62	0.29	0.138	0.848	0.075	−0.034	0.149	0.074	0.009	−0.03	0.104	0.134	0.115
INFOSH6	5.27	1.32	−0.77	0.71	0.189	0.785	0.025	−0.045	0.056	0.106	0.069	0.068	0.154	0.216	0.016
IT Usage																2.751	7.643	0.930
ITUS1	5.53	1.51	−1.0	0.44	0.137	0.012	0.845	0.106	0.061	0.095	0.122	0.212	0.070	0.019	0.034
ITUS2	5.71	1.45	−1.17	0.88	0.146	0.103	0.884	0.119	0.064	0.085	0.036	0.124	0.071	0.131	0.053
ITUS3	5.69	1.34	−1.04	0.68	0.141	0.102	0.847	0.087	0.041	0.068	−0.003	0.229	0.061	0.096	0.046
ITUS4	5.72	1.47	−1.19	0.87	0.057	0.029	0.829	0.137	0.129	0.108	−0.007	0.242	0.028	0.117	0.048
Entrepreneurial orientation (EO)—Innovation																2.164	6.011	0.96
EOINOV1	4.56	1.59	−0.33	−0.49	0.127	0.030	0.143	0.871	0.044	0.251	−0.030	0.116	0.059	0.160	0.035
EOINOV2	4.63	1.60	−0.48	−0.41	0.171	0.019	0.152	0.853	0.030	0.294	−0.055	0.118	0.066	0.172	0.104
EOINOV3	4.64	1.60	−0.38	−0.52	0.169	−0.018	0.189	0.825	0.023	0.306	−0.034	0.135	0.058	0.194	0.086
EO—Proactiveness																1.091	3.030	0.790
EOPROC1	5.83	1.17	−1.17	1.89	0.206	0.120	0.110	0.026	0.197	0.112	0.019	−0.018	0.823	−0.072	0.056
EOPROC2	5.58	1.24	−1.13	1.82	0.212	0.183	−0.022	0.103	0.007	−0.076	−0.018	0.092	0.810	0.116	0.122
EOPROC3	6.06	1.04	−1.40	2.82	0.039	0.303	0.154	0.036	0.299	−0.006	0.022	−0.098	0.681	0.052	0.012
EO—Risk taking																1.144	3.178	0.819
EORT1	4.81	1.80	−0.58	−0.58	−0.104	−0.006	0.233	0.024	−0.057	0.071	0.014	0.810	−0.027	0.165	0.148
EORT2	4.86	1.74	−0.66	−0.41	0.044	0.019	0.322	0.085	0.007	0.155	−0.024	0.831	0.021	0.074	−0.018
EORT3	4.73	1.80	−0.51	−0.83	0.087	0.022	0.331	0.301	0.011	−0.043	−0.001	0.717	0.002	−0.074	−0.105
EO—Autonomy
EOAUT1	5.57	1.30	−1.03	1.15	0.210	0.240	0.022	0.024	0.790	0.027	−0.023	−0.009	0.164	0.222	0.063	2.111	5.864	0.900
EOAUT2	5.83	1.19	−0.87	−0.02	0.265	0.172	0.105	0.003	0.851	0.106	0.052	−0.033	0.145	0.026	0.110
EOAUT3	5.81	1.20	−01.01	0.85	0.240	0.177	0.150	0.069	0.831	0.057	0.084	0.008	0.135	−0.004	0.113
EO—Competitive Advantage																0.837	2.324	0.834
EOCA2	5.44	1.46	−1.06	0.88	0.397	0.081	0.053	0.072	0.319	0.095	0.006	0.002	0.130	0.050	0.749
EOCA3	5.15	1.60	−0.83	0.06	0.407	0.173	0.126	0.134	0.060	0.080	−0.044	0.061	0.099	0.028	0.766
Total variance explained																	81.261
KMO = 0.881; χ2 = 6458.805; df = 630; p < 0.000

in Appendix B, show that all alpha values were greater than the recommended cutoff point of 0.70, representing sufficient consistency in each internal scale. The construct sustainability had fifteen items for measurement, but it was revealed that only seven were supported. All the items that were not supported were removed to obtain a reasonable model fit, achieving Chi-square/df = 827.487/539 = 1.535; RMSEA (Root Mean Square Error of Approximation) = 0.048; CFI (Comparative Fit Index) = 0.954; TLI (Tucker and Lewis) = 0.946; and SRMR (Standardized Root Mean Square Error Residual) = 0.042. This model fit analysis is supported by [58].

Discriminant validity was assessed using the Fornell–Larcker Criterion, which states that the square root of the AVEs should be larger than the correlation of a construct with other constructs.

3.4. Descriptive Statistics, Correlation Results, and Discriminant Validity Assessment

The table below presents the descriptive statistics, correlation results, and the discriminant validity assessment of the various constructs in the study.

3.5. Regression Analysis

The study employed M-Plus version 7.4 to estimate the regression coefficients using the hierarchical approach. This approach is used to assess the individual contributions of the predictors in the model. Six models were estimated, as shown below in

Table 2. Descriptive and construct correlation and discriminant validity results.

Variables	Mean	S.D.	Skew.	Kurt.	1	2	3	4	5	6	7	8	9	10	11	12	13
Firm Age (log) (1)	1.09	0.26	0.13	10.39	1
Firm size (log) (2)	1.73	0.77	0.45	−0.74	0.221 **	1
ENVSUS (3)	4.93	1.41	−0.54	−0.23	0.069	0.064	0.82
SOCSUS (4)	5.06	1.38	−0.71	0.33	0.025	−0.106	0.438 **	0.84
ECOSUS (5)	5.70	1.01	−0.81	0.37	0.213 **	0.040	−0.021	0.108	0.80
SCRES (6)	5.23	1.39	−0.70	−0.05	0.040	−0.010	0.377 **	0.330 **	0.046	0.86
INFOSH (7)	5.33	1.05	−0.50	−0.07	0.009	−0.048	0.306 **	0.255 **	0.057	0.518 **	0.82
ITUS (8)	5.66	1.31	−1.18	0.95	0.022	0.030	0.309 **	0.390 **	0.091	0.333 **	0.192 **	0.88
EOINOV (9)	4.61	1.54	−0.46	−0.36	0.117	−0.050	0.601 **	0.527 **	−0.061	0.369 **	0.143 *	0.373 **	0.94
EOPROC (10)	5.82	0.97	−0.94	1.76	0.004	0.032	0.138 *	0.195 **	0.027	0.429 **	0.436 **	0.214 **	0.189 **	0.75
EORT (11)	4.80	1.53	−0.56	−0.29	−0.046	−0.002	0.231 **	0.286 **	0.004	0.097	0.060	0.554 **	0.348 **	0.044	0.79
EOAUT (12)	5.74	1.12	−0.98	0.86	0.018	−0.085	0.237 **	0.297 **	0.085	0.529 **	0.438 **	0.253 **	0.175 **	0.442 **	0.026	0.87
EOCA (13)	5.29	1.42	−0.92	0.54	0.006	−0.012	0.289 **	0.247 **	−0.010	0.648 **	0.345 **	0.253 **	0.304 **	0.352 **	0.108	0.446 **	0.85

** p < 0.01 level; * p < 0.05; N = 204; square root of AVE shown on the diagonal in bold. Off-diagonal elements are correlations among the constructs and control variables. Source: Authors’ calculations.

and

Table 3. Hierarchical regression model.

Variables	Supply Chain Resilience (Standardized Estimates)			Sustainability (Standardized Estimates)
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Controls
Firm Age (log)	0.044 (0.647)	0.037 (0.629)	0.003 (0.279)	0.094 (1.155)	0.078 (0.999)	0.001 (0.052)
Firm size (log)	0.027 (0.397)	0.002 (0.040)	0.008 (0.279)	0.037 (0.393)	0.016 (0.186)	0.003 (0.052)
Independent Variable
Information Sharing (IS)		0.545 (10.706) **	0.493 (9.191) **	0.442 (5.649) **	0.209 (2.172) *	0.004 (0.052)
Mediator
SC Resilience					0.430 (4.687) **	0.149 (0.974)
Moderators
IT Usage (ITUS)			0.254 (4.415) **
Entrepreneurial Orientation (EO)						0.655 (3.050) **
Interaction Effect
IS X ITUS			0.010 (0.279)
SCRES X EO						0.008 (0.094)
Fit indices
R2	0.002	0.299	0.362	0.204	0.332	0.478
∆R2		0.297	0.063		0.128	0.146
χ2/d.f	29.061/13 = 2.24	104.329/52 = 2.01	†	142.645/85 = 1.68	251.814/163 = 1.54	†
RMSEA	0.072	0.065	†	0.054	0.048	†
CFI	0.984	0.972	†	0.965	0.968	†
TLI	0.975	0.964	†	0.957	0.962	†
SRMR	0.024	0.038	†	0.052	0.048	†
Direct effect path		Mediator	Effect	Boot SE ⸸	95% Confidence Interval
Information Sharing → Sustainability		⸺	0.208	0.117	0.025 to 0.402
Indirect effect path
Information Sharing → Sustainability		Supply Chain Resilience	0.234 **	0.065	0.347 to 0.421
Total effect
Information Sharing → Sustainability			0.443 **	0.117	0.252 to 0.622

** p-value < 0.01, * p-value < 0.05; † results not available for algorithm = integration function in Mplus 7.4; ⸸ 5000 bootstrapping. Source: Authors’ calculations.

. The results of Model 2 estimate the relationship between the independent variable (information sharing) and the dependent variable (sustainability), while controlling for the effect of the control variables. The results indicate that information sharing has a significant relationship with supply chain resilience (β = 0.545, t = 10.71, p < 0.05). To test the moderating role of technological tool usage in the relationship between information sharing and supply chain resilience, Model 3 was estimated. The results of Model 3 suggest that the interaction effect of information sharing and technological tool usage on supply chain resilience is not significant (β = 0.010, t = 0.28, p > 0.05). This implies that hypothesis 3 (H3) is rejected. Moreover, Model 4 was estimated to examine the relationship between supply chain resilience and sustainability, while controlling for the effect of the control variables. The results indicate that supply chain resilience has a significant positive relationship with sustainability (β = 0.430, t = 4.69, p < 0.05).

In addition, to estimate the moderating role of entrepreneurial orientation in the relationship between supply chain resilience and sustainability, Model 6 was computed. The results indicate that entrepreneurial orientation does not positively moderate this relationship (β = 0.008, t = 0.09, p > 0.05) (Figure 2). This leads to the rejection of hypothesis 3 (H3). The results of Model 4 indicate that information sharing has a direct positive relationship with sustainability (β = 0.442, t = 5.65, p < 0.05), which confirms hypothesis 1 (H1). A bootstrap confidence interval using 5000 samples was used to test the mediation effect. The results suggest that supply chain resilience positively mediates information sharing and sustainability (β = 0.442, t = 5.65, p < 0.05).

Considering that the direct effect is still significant after introducing the mediator into the model, this mediation can be considered a partial mediation.

4. Discussion of Findings and Implications

This research addresses four key objectives, which are (1) to study the relationship between information sharing and sustainability in an organization; (2) to assess the mediating role of resilience in the relationship between information sharing and sustainability; (3) to examine the moderating role of technological tool usage in the relationship between information sharing and supply chain resilience in an organization’s supply chain practices; (4) to ascertain the relationship between resilience and sustainability, necessitating the introduction of a moderator, which is entrepreneurial orientation. Survey data from industries in some regions of Ghana, including mining, extraction, manufacturing, distribution, and service industries, were selected. Using stakeholder theory and complementary insight from information processing theory (IPT), this study finds a significant direct relationship between information sharing and sustainability. Additionally, the mediating role of resilience has a direct relationship with information sharing and sustainability. This direct relationship indicates that information is essential, as stated in the literature, in achieving sustainability. Sharing information among network partners will enhance sustainability and increase the firm’s performance. As noted in prior studies [61], stakeholder theory is a corporate management theory that considers the broader coverage of factors influencing firms in diverse ways, nationally and internationally.

However, one of the shortcomings of this study was that neither of the moderating variables, which were entrepreneurial orientation and information technology tool usage, had a significant direct effect on the relationships. Hence, the findings suggest that, in line with the moderating role of IT tool usage, organizations must train their staff to use IT tools to their full capacity, and focal firms should capitalize on the idea that IT tools enhance information sharing and resilience strategies. In addition, workflows and procedures must frequently change when new IT tools are introduced. Because they are accustomed to the current information sharing procedures, fear the unknown, or worry about their job security, some individuals may oppose these changes. The company culture is an essential factor in influencing whether or not employees are willing to accept new technologies in an existing organizational culture. Successfully implementing IT solutions could be challenging if the company culture resists change or favors conventional forms of communication and information sharing [62].

The study further revealed the lack of a considerable direct relationship between the moderating role of entrepreneurial orientation and the relationship between resilience and sustainability. Though data on the moderating role of entrepreneurial orientation was scant, this study wanted to ascertain the reason for such a gap in the literature. So, it has come to light that other factors, as stated in existing data, including supply chain ambidexterity and supply chain agility, proactive capability, reactive capability, and supply chain design, can explain the relationship better than EO. The significant indirect relationship may have also occurred due to the definition of the variable, where building redundancy, flexibility, and adaptability within the company to respond to unforeseen events and difficulties is a common component of resilience methods. In conclusion, entrepreneurial orientation can affect strategic decision-making and organizational behavior, but it plays a complicated and context-specific role in modulating the linkages between sustainability and resilience. Ensuring long-term viability and success requires organizations to navigate the dynamic interplay between these notions, which involves several elements and trade-offs.

5. Conclusions

This study examines the relationship between information sharing and the sustainability of an organization, which show a positive relationship. This means that information sharing is a major driver of the supply chain, as stated in the existing literature. Resilience was also established to have a significant direct effect on the relationship between information sharing and sustainability.

The role of information technology tool usage or digitalization in the information sharing and resilience relationship, though having a significant indirect impact in this study, encourages managers to implement other measures for employees to understand the benefits of technological tool usage in achieving effective communication and resilience strategies. The outcomes can inspire managers to enforce policies for insightful action geared towards collaboration and environmental/social/economic performance across the supply chain. Such policies comprise sustainable supply chain and partner engagement policies (like capacity-building programs), social and ecological impact monitoring policies (like community engagement policies, regular audits of labor standard compliance), and technological investment policies that will support digital tool usage, enabling real-time information sharing.

The risks associated with globalization that the selected firms in this study face include diverse regulatory environments, especially in the mining industries; complexity in supply chain networks in distribution industries; and lack of transparency, traceability, and visibility, especially for suppliers in the manufacturing industries selected in this study. Frequent transportation of goods and services leads to higher carbon emissions in all the firms chosen for this research, since they are all involved in global business. Again, companies face the risk of disruptions (pandemics, political unrest, war), barriers in communication, and cultural differences. Nevertheless, though these challenges and risks can adversely affect firms, this study established, in its findings, measures that companies can implement. The measures include encouraging the use of flexible contract agreements, allowing for quick switches or adjustments due to disruptions; instituting resilience protocols that have been pre-defined with providers or suppliers when faced with crises; diversifying suppliers across tiers; changing organizational culture towards digital tool usage; rewarding employees or partners engaging in the accurate use of tools; encouraging supply chain partners to think creatively; and co-creating sustainable solutions with supply chain partners, like designing new products.

Management must never forget that sustainability must involve the triple bottom line: the environment, society, and the economy. The study supported this triple bottle line, and the companies under study understood the Sustainable Development Goals of Agenda 2030. Additionally, managers are highly recommended to embrace resilience measures in their operations. Management should educate and train employees to use information technology tools to achieve organizational performance. Entrepreneurial orientation, which involves innovativeness, proactiveness, risk-taking, autonomy, and competitive aggression, should be shared among stakeholders [43]. Though the moderating influence of entrepreneurial orientation was not supported, the idea of entrepreneurial orientation is already known, and management should invest in it. The study adds input to the existing literature on the information sharing and sustainability relationship, which showed a positive result. It is suggested that organizational strategies geared towards sustainability lead to firms gaining a competitive advantage in the business environment.

The study was limited to selected industries in Ghana, which restricted the responses; further studies can expand the scope to other sectors like textiles and apparel. The selected regions were also a limitation in this study due to time constraints; further studies can expand on this. Further studies can also investigate the moderating influence of entrepreneurial orientation on Small and Medium-sized (SME) companies, since they practice these strategies more than large and multinational companies. Also, EO measurements in the literature are generally limited to innovativeness, proactiveness, risk-taking, autonomy, and competitive aggressiveness. Still, other sustainable traits like ethical responsiveness, adaptability, and flexibility can be researched. Likewise, EO can be contextually influenced by institutional settings and national culture, but these are not examined. Lastly, most industrial and sustainable research, like this study, relies on managers or senior supervisors, which may lead to respondent bias, among other advantages of managers’ processes. Further studies can sample other levels of the workforce.