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There is a tremendous need for the valuation of small businesses. Oftentimes, small businessowners do not have the wherewithal to gather the data and keep it up to date for use in situations that require valuation. Formal valuations are necessary because they provide objective evidence of value, in contrast to value set by markets on which public companies are traded. This article focuses on some factors that impact the valuation of the business and will help small businessowners feel more comfortable talking with financial professionals about how the business might be valued.

While considerable attention has been devoted to the personality traits of entrepreneurs, less attention has been given to their values, especially outside of a Western context. Values are instrumental in the decision to pursue entrepreneurship, and have implications for the entrepreneurʼs approach to creating and managing the venture. The role of values would seem especially relevant in the context of ethnic subcultures. Values traditionally associated with entrepreneurship, such as risk, individualism, competitiveness, wealth generation, and growth, may be more consistent with Western cultures, and may conflict with closely held values within various ethnic subcultures the world over. This article examines the values of entrepreneurs in two ethnic subcultures within South Africa. Findings are reported from interviews with cross-sectional samples of black and colored entrepreneurs. The results indicate entrepreneurs tend to embrace common values regardless of their individual ethnic heritage, but with different underlying patterns. In addition, the entrepreneurial path itself gives rise to certain shared values; and the overarching country culture has a strong influence on value orientations. Implications are drawn from the results, and suggestions made for ongoing research

The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.

The authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.

The results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.

As research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.

The study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.

As managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.

This study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

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.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

The aim of this paper is to review and synthesise the recent advancements in the business model literature and explore how firms approach business model innovation.

A systematic review of business model innovation literature was carried out by analysing 219 papers published between 2010 and 2016.

Evidence reviewed suggests that rather than taking either an evolutionary process of continuous revision, adaptation and fine-tuning of the existing business model or a revolutionary process of replacing the existing business model, firms can explore alternative business models through experimentation, open and disruptive innovations. It was also found that changing business models encompasses modifying a single element, altering multiple elements simultaneously and/or changing the interactions between elements in four areas of innovation: value proposition, operational value, human capital and financial value.

Although this review highlights the different avenues to business model innovation, the mechanisms by which firms can change their business models and the external factors associated with such change remain unexplored.

The business model innovation framework can be used by practitioners as a “navigation map” to determine where and how to change their existing business models.

Because conflicting approaches exist in the literature on how firms change their business models, the review synthesises these approaches and provides a clear guidance as to the ways through which business model innovation can be undertaken.

This study aims to investigate the favourable conditions that influence transgenerational value transmission (TVT), value acceptance and value similarity between generations in indigenous African business-owning families.

This study adopts a multiple case study design and draws on semi-structured face-to-face interviews to collect data from participants in seven indigenous Black business-owning families located in South Africa. The software ATLAS.ti was utilised to manage the data and reflexive thematic analysis was undertaken.

The analysis reveal four themes describing how transmission factors facilitate favourable conditions for successful TVT in IBSA business-owning families, namely, authoritarian parenting, a loving and connected family relational climate, the continuous reinforcement of autonomy during childhood development and family authenticity in the face of societies dominant values climate. Furthermore, value similarity is perceived to exist among the different family generations in the business-owning families.

This study is among the first to adopt the value acquisition model to empirically examine successful TVT and examine the extent of value similarity or dissimilarity, using the business-owning family as the unit of analysis. Novel contributions to family business literature and practices are proposing a model for TVT in an African context and studying relationships from a business-owning family perspective. The model for TVT could be used to socialise the NextGen members into value sets and behaviours that help business-owning families preserve their entrepreneurial legacy and family business longevity.

Customer value perception of Internet of Things (IoT)-based services has not been studied in the context of a company’s readiness to adopt IoT technology. The purpose of this paper is to address this gap by indicating a research framing that combines insights from the IoT business model literature and customer perception of the value of such models and their drivers.

The interplay between a company’s IoT readiness and its perception of the value of IoT services is tested using a sample of 90 Eastern European business customers in a competitive business field. The conceptual framework described also examines relationships among constructs that refer to relationship quality. This study evaluates its quantitative sample using partial least squares path modeling.

Customers’ perceived value of IoT business models strongly relates to their digitalization capabilities and their own company’s innovativeness. When referring to disruptive technical offerings, existing trustful and satisfactory relationships cannot enhance the customer’s value perception.

The sample of Eastern European buyers is not representative of the majority of manufacturing companies. A randomized sample using other sources such as large industry databases could be useful. In addition, a replication of the study in other countries would allow for a cross-border validation of this study’s results.

This study suggests a detailed process that is based on a careful preselection of test customers working for innovative companies. A marketing communication approach must state clearly the benefits the buyers get in return for their sacrifice of sharing data.

Technology readiness refers to the user’s propensity to embrace and use new technologies. The results indicate that IoT readiness influences the successful launch of IoT-related business models. For managers, this study proposes a process to implement IoT-related business models.

This study aims to synthesize the body of sustainable value creation (SVC) research within sustainable business model literature through a systematic literature review.

A systematic literature review of 85 research articles of SVC through business models from 2011 to 2020.

The systematic literature review allowed the authors to identify five core SVC elements: value forms, stakeholders, temporal view, spatial view and tensions and conflicts. Moreover, a conceptual framework presenting the interrelationships of the SVC elements is proposed.

This study carries implications for practitioners in the form of guiding questions provided in the framework. Those questions help responsible managers to plan, identify and choose strategic sustainability actions and to develop companies’ business models aiming to lead to the creation of long-term sustainable value in different time frames and locations or different parts of the value network. Additionally, the framework guides managers to identify and manage potential tensions and conflicts which can otherwise hinder SVC.

To the best of the authors’ knowledge, this study is the first systematic literature review of SVC through business models with the conceptual development of SVC. The study synthesizes the fragmented literature to identify SVC elements and build basis for conceptualization of SVC through business models.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.