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Gillette’s historically successful “razor and blade” business model (RBM) has been a promising benchmark for multiple businesses across diverse industries worldwide in the past several decades. The extant literature deals with very few nuances of this business model notwithstanding the fact that there are several variants of this business model being put to practical use by firms in diverse industries in grossly metaphorically equivalent situations.

This study adopts the 2 × 2 truth table framework from the domains of mathematical logic and combinatorics in fleshing out all possible (four logical possibilities) variants of the razor and blade business model for further analysis. This application presents four mutually exclusive yet collectively exhaustive possibilities on any chosen dimension. Two major dimensions (viz., provision of subsidy and intra- or extra-firm involvement in the making of razors or blades or both) form part of the discussion in this paper. In addition, this study synthesizes and streamlines entrepreneurial wisdom from multiple intra-industry and inter-industry benchmarks in terms of real-time firms explicitly or implicitly adopting several variants of the RBM that suit their unique context and idiosyncratic trajectory of evolution in situations that are grossly reflective of the metaphorically equivalent scenario of razor and recurrent blades. Inductive method of research is carried out with real-time cases from diverse industries with a pivotally common pattern of razor and blade model in some form or the other.

Several new variants of the razor and blade model (much beyond what the extant literature explicitly projects) have been discovered from the multiple metaphorically equivalent cases of RBM across industries. All of these expand the portfolio of options that relevant entrepreneurial firms can explore and exploit the best possible option chosen from them, given their unique context and idiosyncratic trajectory of growth.

This study has enriched the literature by presenting and analyzing a more inclusive or perhaps comprehensive palette of explicit choices in the form of several variants of the RBM for the relevant entrepreneurial firms to choose from. Future research can undertake the task of comparing these variants of RBM with those of upcoming servitization business models such as guaranteed availability, subscription and performance-based contracting and exploring the prospects of diverse combinations.

Smart entrepreneurial firms identify and adopt inspiring benchmarks (like razor and blade model whenever appropriate) duly tweaked and blended into a gestalt benchmark for optimal profits and attractive market shares. They target diverse market segments for tied-goods with different variants or combinations of the relevant benchmarks in the form of variegated customer value propositions (CVPs) that have unique and enticing appeal to the respective market segments.

Value-sensitive customers on the rise globally choose the option that best suits them from among multiple alternatives offered by competing firms in the market. As long as the ratio of utility to price of such an offer is among the highest, even a no-frills CVP may be most appealing to one market segment while a plush CVP may be tempting to yet another market segment simultaneously. While professional business firms embrace resource leverage practices consciously, amateur customers do so subconsciously. Each party subliminally desires to have the maximum bang-to-buck ratio as the optimal return on investment, given their priorities ceteris paribus.

Prior studies on the RBM have explicitly captured only a few variants of the razor and blade model. This study is perhaps the first of its kind that ferrets out many other variants (more than ten) of the razor and blade model with due simplification and exemplification, justification and demystification.

This study aims to develop a model for coordination and communication overhead in distributed software development through case study analysis in the Indian outsourcing software industry. The model is based on business knowledge, which can be classified as domain, regulatory, strategic, business process and operation process knowledge as per existing literature.

Double case study method was used to verify an existing knowledge–management framework of software development from the literature. The stakeholders of both the cases were interviewed, and project documents were verified to reach conclusions.

The findings supported the business knowledge classification from the literature. The concept can be used to analyze the software project in a distributed environment.

The research work findings are based only on two case studies. The study findings cannot be generalized and should be used as a learning tool. There can be large variations of project characteristics with differences in business knowledge requirements. The research shows the importance of business knowledge transfer in global software development.

Projects managers in the distributed software development environment can use the findings in project planning and work allocation for better control over cost and schedule, etc.

There is little research works attempted to study the business knowledge classification in the global software industry making the research novel.

This study analyzes how tech firms can implement the modern wave of subscription-based business model (SBBM), including value proposition, value creation, value capture and performance. In fact, these elements push tech firms to move from traditional to SBBMs.

To achieve the objectives of this study, we initially construct a theoretical framework for applying SBBM. Subsequently, we employ qualitative research to examine the current implementation of the subscription-based economy within tech firms.

A successful SBBM necessitates capturing value through sustainable revenue transactions and revising aspects of the value proposition, creation and capture. Continuous improvement through business value analysis is imperative. Additionally, an agile operations system is vital to address revenue complexities, enable data collection and enhance value proposition, service innovation, churn rate and customer retention, which are essential for SBBM maintenance.

This study delves into how the subscription-based economy is reshaping the business models of tech firms. Beyond exploring the theoretical foundation of this transformative path, this study offers actionable insights on enhancing the value proposition, creation, capture and business value within subscription-based economy frameworks.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

The purpose of this research study is to empirically investigate the Figma prototyping technology adoption factors among entrepreneurship and innovation libraries for providing support to startups by developing and evolving the prototype solutions in collaboration with health libraries.

This study uses the technology adoption model (TAM) as a framework and the partial least squares structural equation modeling (PLS-SEM) method of structural equation modeling (SEM) using SmartPLS 3.2.9 software version to investigate the prototyping adoption factors among entrepreneurship and innovation libraries for rural health innovations. A total of 40 libraries, spread over 16 entrepreneurship and innovation libraries, participated in this survey, including participants from Europe (35%), Asia (15%) and USA (50%).

The findings show that previous experience, social impact, brand image and system quality have a significant positive impact on entrepreneurship and innovation libraries' perceived usefulness (PU) of prototyping technology. Perceived ease of use of prototype technology is positively influenced by usability, training materials and documentation, experience and self-efficacy. Together, perceived usefulness and perceived ease of use have a significant influence on behavioural intention. Behavioural intention is positively impacted by minimal investment and shallow learning curve. Technology adoption is furthered by behavioural intention. The control variables, for instance location, gender and work experience (as librarian), were found not having any impact on Figma technology adoption.

Through strategic partnerships with other libraries (including health libraries), policymakers, and technology providers, the adoption of prototype technology can be further accelerated. The important ramifications for policymakers, technology providers, public and entrepreneurship and innovation libraries to create a self-reliant innovation ecosystem to foster rural health innovation based on entrepreneurship are also listed in the article.

This research is distinctive since it integrates several areas of study, including entre, advances in rural healthcare and libraries. A novel idea that hasn't been thoroughly investigated is the collaboration between entrepreneurship and innovation libraries and health libraries for supporting businesses. This study offers insights into the factors that drive technology adoption and offers practical advice for policymakers and technology providers. It also advances understanding of the adoption of Figma prototyping technology among libraries for rural health innovation. Overall, this study provides a novel viewpoint on the nexus between different disciplines, showing the opportunity for cooperation and innovation in favour of rural health.

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.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

The current gap between the required and available artificial intelligence (AI) professionals poses significant challenges for organisations and academia. Organisations are challenged to identify and secure the appropriate AI competencies. Simultaneously, academia is challenged to design, offer and quickly scale academic programmes in line with industry needs and train new generations of AI professionals. Therefore, identifying and structuring AI competencies is necessary to effectively overcome the AI competence shortage.

A probabilistic topic model was applied to explore the AI competence categories empirically. The authors analysed 1159 AI-related online job ads published on LinkedIn.

The authors identified five predominant competence categories: (1) Data Science, (2) AI Software Development, (3) AI Product Development and Management, (4) AI Client Servicing, and (5) AI Research. These five competence categories were summarised under the developed AI competence framework.

The AI competence framework contributes to clarifying and structuring the diverse AI landscape. These findings have the potential to aid various stakeholders involved in the process of training, recruiting and selecting AI professionals. They may guide organisations in constructing a complementary portfolio of AI competencies by helping users match the right competence requirements with an organisation's needs and business objectives. Similarly, they can support academia in designing academic programmes aligned with industry needs. Furthermore, while focusing on AI, this study contributes to the research stream of information technology (IT) competencies.

The aim of this paper is to evaluate the intensity and success of the digitalization process, by measuring the efficiency of the use of information and communication technologies in business in the Republic of Serbia (RS) in the period from 2006 to 2019.

The data envelopment analysis method is applied and due to the sensitivity of the results to measurement errors, the robustness analysis of the obtained values of average efficiency is performed, using the bootstrapping method.

The results show an intensive, expansive and relatively efficient process of digital business transformation in the RS. The results indicate inefficient use of software packages, While the efficiency of e-commerce in companies in most years is over 80%.

The research is limited to the RS, so the conclusions cannot be generalized in a broader context.

The biggest problem in the implementation of digital business transformation in the RS is the understanding of management and employees in organizations that digital business transformation will take place only if software solutions are purchased and installed, with less attention paid to their proper application and low use of their maximum capabilities.

Digital transformation measurement is the subject of a very small number of studies. Through a review of the literature, the authors of this paper do not find the use of data envelopment analysis to measure the efficiency of digital business transformation in the way they present it in this paper.

This study reviews scholarly work in sustainable green logistics and remanufacturing (SGLR) and their subdisciplines, in combination with bibliometric, thematic and content analyses that provide a viewpoint on categorization and a future research agenda. This paper provides insight into current research trends in the subjects of interest by examining the most essential and most referenced articles promoting sustainability and climate-neutral logistics.

For the literature review, the authors extracted and sifted 2180 research and review papers for the period 2008–2023 from the Scopus database. The authors performed bibliometric and content analyses using multiple software programs such as Gephi, VOSviewer and R programming.

The SGLR papers can be grouped into seven clusters: (1) The circular economy facets; (2) Decarbonization of operations to nurture a climate-neutral business; (3) Green sustainable supply chain management; (4) Drivers and barriers of reverse logistics and the circular economy; (5) Business models for sustainable logistics and the circular economy; (6) Transportation problems in sustainable green logistics and (7) Digitalization of logistics and supply chain management.

In this review, fundamental ideas are established, research gaps are identified and multiple future research subjects are proposed. These propositions are categorized into three main research streams, i.e. (1) Digitalization of SGLR, (2) Enhancing scopes, sectors and industries in the context of SGLR and (3) Developing more efficient and effective climate-neutral and climate change-related solutions and promoting more environmental-related and sustainability research concerning SGLR. In addition, two conceptual models concerning SGLR and climate-neutral strategies are developed and presented for managers and practitioners to consider when adopting green and sustainability principles in supply chains. This review also highlights the need for academics to go beyond frameworks and build new techniques and instruments for monitoring SGLR performance in the real world.

This study provides an overview of the evolution of SGLR; it also clarifies concepts, environmental concerns and climate change practices, particularly those directed to supply chain management.