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This study aims to explore how the top 50 Australian companies are disclosing their commitment to addressing the sustainable development goals (SDGs) formulated by the United Nations (UN) in 2015. By investigating the nature and substantiveness of SDG reporting, this study provides exploratory evidence on how companies are taking the initial steps to addressing the SDGs.

A content analysis of SDG disclosures by the top 50 Australian companies was undertaken. This content analysis was guided by the KPMG (2018) SDG disclosure framework. Legitimacy theory was used to interpret the findings, establishing whether such disclosure was substantive or symbolic.

This study reports a moderate level of SDG disclosure among Australian companies. The top five most critical SDGs in Australian context are climate action, gender equality, decent work and economic growth, responsible consumption and production and industry, innovation and infrastructure. The findings also highlight that while the focus of Australian companies is on understanding and prioritizing SDGs, the measurement of SDGs performance needs to increase.

This study adds to limited literature on the corporate responses to SDGs by establishing how companies, especially in Australia, are addressing these goals through changes to their reporting systems, thereby communicating their strategic intent in relation to addressing these goals. A focus on symbolic legitimation through SDG disclosure by the Australian companies in this study reaffirms the findings of similar studies and suggests a need for more substantive SDG management and disclosure if these goals are to be adequately addressed by the corporate sector.

The findings of this study provide insights into the current practices and future prospects of corporate responses to SDGs. Policy implications could arise in relation to possible approaches for disclosing social and environmental information and the paper argues for a potential need for regulation of non-financial reporting.

This study contributes to the limited understanding of the corporate response to an urgent sustainability call made by the UN by providing evidence on how Australian companies are embedding, measuring and reporting the SDGs. The research goes beyond a descriptive analysis of SDG disclosure and assesses whether such disclosure is substantive or symbolic.

This study aimed to discover the factors affecting employee performance by testing the relationship of change management, job satisfaction, organizational commitment and leadership style on employee performance in Indonesian sharia property companies.

The study population was all members of “Sharia Property Developer” (DPS) across Indonesia with criteria of having subordinates at least one person and is listed as a DPS member. The samples used were 71 people from the 200 members of DPS across Indonesia. The sampling method used was based on R² value and significance level with an 80% statistical strength. Data analysis was carried out using smartPLS software to test the relationship of change management, job satisfaction, organizational commitment and leadership style on employee performance.

The utilization of SEM in Smart PLS for change management with the ADKAR method had a negative value of 6.2% in affecting employee performance and 4.6% in affecting job satisfaction. Job satisfaction insignificantly affected employee performance by 7.5%. Leadership style and organizational commitment positively affected performance by 57.9% and 25.6%, respectively.

This study did not limit respondents’ education levels. Twenty percent of respondents were middle and high school graduates. Respondent’s position was mostly the highest leader in the company by 58%. Indicators in the ADKAR model did not implement the construct validity test since the researchers did not find precedent studies that discuss the indicators of the ADKAR model in detail.

Factors that positively and significantly affected employee performance can be used to plan employee performance of DPS member companies.

The company must create a program to produce meaning in working, shape leaders to have discipline by putting appropriate employees as leaders.

This study used change management, organizational commitment, job satisfaction and leadership style as exogenous variables, job satisfaction and leadership style as intervening variables. The study model modified the previous study regarding employee performance improvement because it utilized the change management with the ADKAR model. The study objects were sharia property companies, where the researchers did not find previous studies discussing employee performance in sharia property companies.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

Firms are increasingly pressured to comply with mandatory supply chain transparency (SCT) regulations. Drawing on information processing theory (IPT), this study aims to show how blockchain technology can address information uncertainty and equivocality in assuring regulatory compliance in an interorganizational network (ION).

IPT is applied in a single case study of an ION in the mining industry that aimed to implement blockchain to address mandatory SCT regulations. The authors build on a rich proprietary data set consisting of interviews and substantial secondary material from actors along the supply chain.

The case shows that blockchain creates equality between actors, enables compliance and enhances efficiency in an ION, reducing information uncertainty and equivocality arising from conflict minerals regulation. The system promotes engagement and data sharing between parties while protecting commercial sensitive information. The lack of central authority prevents larger partners from taking control. The system provides mineral provenance and a regulation-compliant record. System cost analysis shows that the system is efficient as it is inexpensive relative to volumes and values of metals transacted. Issues were identified related to collecting richer human rights data for assurance and compliance with due diligence regulations.

The authors provide some of the first evidence in the operations and supply chain management literature of the specific architecture, costs and limitations of using blockchain for SCT. Using an IPT lens in an ION setting, the authors demonstrate how blockchain-based systems can address two key IPT challenges: environmental uncertainty and equivocality.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

The demand for halal food products is increasing globally. However, fraudulent activities in halal products and certification are also rising. One strategy to ensure halal integrity in the food supply chain is applying halal blockchain technology. However, to date, a few studies have assessed the factors and variables that facilitate or hinder the adoption of this technology. Thus, this study aims to assess the significant factors and variables affecting the adoption of halal blockchain technology.

A Delphi-based approach, using semi-structured interviews, was conducted with three food companies (chicken slaughterhouses, milk processing plants and frozen food companies). The cognitive best–worst method determines the significant factors and variables to prioritise halal blockchain adoption decisions.

The results showed that the most significant factors were coercive pressure and halal strategy. Nineteen variables were identified to establish a valid hierarchical structure for halal blockchain adoption in the Indonesian food industry. The five significant variables assessed through the best–worst method were demand, regulator, supply side, sustainability of the company’s existence and main customers.

The proposed halal blockchain decision structure can assist food companies in deciding whether to adopt the technology.

This study proposes 19 variables that establish a valid hierarchical structure of halal blockchain adoption for the Indonesian food industry.

Timber waste from construction is downcycled into non-structural products, incinerated for energy generation or disposed of in landfills. Existing literature highlights that the use of reprocessed timber for structural purposes is limited. Therefore, this study aims to focus on identifying factors limiting reprocessed structural timber (RST) uptake amongst construction professionals in Australia.

Current literature shows that the use of reprocessed materials (RMs) depends on user-specific personal factors and broader contextual factors. Therefore, data collection and analysis were based on the attitude-behaviour-context (ABC) theory, which affirms this relationship between personal and contextual factors in determining pro-environmental behaviours (PEBs). A qualitative research approach was adopted, considering limitations with industry expertise and the need for developing an in-depth understanding of limiting factors. Twenty semi-structured interviews were conducted amongst construction professionals experienced in using reprocessed materials, while the thematic analysis technique was used to analyse interview findings.

Personal factors that limit the uptake of RST include negative cost and quality perceptions, risk appetite, the tendency to maintain the status-quo, limited decision-making capability and lack of skills and expertise, while contextual factors include higher prices, poor and uncertain quality, limitations with information availability, under-developed supply and drawbacks in the regulatory environment.

The current study is amongst the first to explore the uptake of reprocessed timber for structural uses in Australia. The findings can be utilised to create a stronger demand for RST by directly addressing personal and contextual factors that constrain construction professionals from using RST.

This chapter focuses on organizational preservation and curation capabilities. The authors define capabilities and explain how they pertain to an enterprise architecture. The authors describe preservation as it is currently practiced in relation to information and data. They also explain how preservation should be expanded to cover knowledge assets. Knowledge preservation exists today as a support capability, aligned with information and data management. Curation is described as an emerging but fragmented practice. It is modeled as a new business capability.

In an era where sustainability and digital transformation are becoming indispensable pillars of successful business operations, this chapter explores the potent synergy between these two paradigms. As businesses strive to align their operations with Environmental, Social, and Governance (ESG) goals, digital transformation emerges as a powerful enabler. This chapter delves into how digital technologies are not only revolutionizing traditional business models but are also paving the way toward more sustainable practices. From data-driven decision-making to improved resource management, this chapter discusses the diverse ways in which digital transformation contributes to sustainability. It also offers an in-depth analysis of real-world case studies, illustrating how businesses have successfully integrated digital transformation in their pursuit of sustainability. Recognizing the potential roadblocks, this chapter also addresses the challenges businesses may face in this journey, including cybersecurity risks, data privacy issues, and the need for technological literacy. It further presents strategies to navigate these challenges and underscores the importance of preparedness in managing potential risks. Finally, this chapter ventures into the future of digital transformation, evaluating current trends and predictions, and their potential impact on sustainable business practices.