Assessing Business Model Performance Using Scalability and Replicability as Performance Indicators: A Case of an Electric Commercial Vehicle Ecosystem

In recent decades, the concept of a business model (BM) has attracted much attention as a strategic tool for understanding firm competitiveness. As organizations face increasing complexities and uncertainties, assessing performance of BMs has become increasingly important for understanding how firms can leverage their strengths, address weaknesses, and adapt to changing industry dynamics. However, assessing BMs’ performance presents inherent challenges due to multifaceted dimensions and quantification complexities, as well as the absence of well-defined and appropriate performance indicators. This study thus responds to the recent calls for research on assessing BMs’ performance by proposing an assessment framework using two BM outcomes, scalability and replicability, as potential performance indicators. Using an electric commercial vehicle (ECV) ecosystem as a case study, we employ an assessment framework, exploring the determinants of scalability and replicability in ECV BMs, which are then categorized as technical, economic (or business-oriented), and regulatory. This article contributes to the emerging BM literature by proposing scalability and replicability as two performance indicators for a comprehensive understanding of BM performance. It further illuminates both concepts of scalability and replicability, concluding with practical implications for managers designing scalable and replicable BMs.

Abstract-In recent decades, the concept of a business model (BM) has attracted much attention as a strategic tool for understanding firm competitiveness.As organizations face increasing complexities and uncertainties, assessing performance of BMs has become increasingly important for understanding how firms can leverage their strengths, address weaknesses, and adapt to changing industry dynamics.However, assessing BMs' performance presents inherent challenges due to multifaceted dimensions and quantification complexities, as well as the absence of well-defined and appropriate performance indicators.This study thus responds to the recent calls for research on assessing BMs' performance by proposing an assessment framework using two BM outcomes, scalability and replicability, as potential performance indicators.Using an electric commercial vehicle (ECV) ecosystem as a case study, we employ an assessment framework, exploring the determinants of scalability and replicability in ECV BMs, which are then categorized as technical, economic (or business-oriented), and regulatory.This article contributes to the emerging BM literature by proposing scalability and replicability as two performance indicators for a comprehensive understanding of BM performance.It further illuminates both concepts of scalability and replicability, concluding with practical implications for managers designing scalable and replicable BMs.

I. INTRODUCTION
I N TODAY's business landscape, the concept of business model (BM) has emerged as a fundamental imperative that underpins how companies operate in the market, and how they create value [1], [2], [3].In this context, the assessment of BMs becomes increasingly important for determining how BMs perform in dynamic environments [4], [5].Assessing BMs' performance helps firms identify their strengths and weaknesses.This assessment enables firms to leverage their core competences and address areas requiring improvement [6].By identifying value proposition, key resources and capabilities, firms can optimize operations to strengthen their competitiveness.BM evaluation process also extends to assessing business partners' capabilities (e.g., in the business ecosystem or value chain), which helps firms gain insights into their partners and identify areas for collaboration and improvement.Furthermore, BM assessment can provide valuable insights into external environmental factors that result in opportunities or threats.For example, companies can identify emerging market trends, technological advances, regulatory changes, and competitive dynamics that may impact their BM.
While the need to assess the performance of BMs is widely recognized, the extant BM literature does not emphasize performance as a major focus [7], [8], [9].Rather, the literature has traditionally addressed the performance of a firm's BMs by examining different financial aspects and indicators, including profit generation, revenue growth, novel value, and efficiency, as well as value capture, adjustability, and risk mitigation [3], [10], [11].However, nonfinancial indicators are seldom discussed [12], [13].This study's main objective is therefore to explore how BM performance is evaluated in the electric commercial vehicle (ECV) ecosystem.Specifically, we seek to identify the key performance indicators (KPIs) that firms use to effectively measure their BM performance.
The ECV ecosystem presents a pertinent case study for studying a firm's BM performance.As transport transitions to electrification, the commercial vehicle sector is experiencing a paradigm shift due to technological advances, changing regulatory frameworks, and the increasing demand for sustainable transport solutions [14].Studying the concept of performance in this context is crucial, as it provides insights into the effectiveness of transitioning to electrification.In this transformative context, a performance assessment serves as a means to measure successful integration and identifying potential bottlenecks [15], [16].Moreover, understanding the performance implications becomes even more crucial for stakeholders, helping them navigate multifaceted challenges, leverage emerging opportunities, and ensure their BMs' long-term viability and success in such a dynamic environment [16].
This study therefore responds to the recent calls for research on assessing BM performance by proposing two outcomes of BMs, scalability and replicability, as performance indicators.Scalability generally denotes an organization's ability to expand its size while still performing effectively under increased workloads [17].In this context, scalability refers to a BM's internal growth potential and flexibility [17], [18].Meanwhile, replicability is defined as the firm's ability to duplicate the success of a business or strategy in different contexts or situations [19].It denotes the degree of external flexibility to adapt to various contextual requirements [19], [20], [21].This study aims to develop an assessment framework of BM performance, emphasizing scalability and replicability as performance indicators.The article applies the developed framework to explore the determinants of scalable and replicable BMs in a case study of an ECV ecosystem, which creates and tests new and innovative BMs for fleet electrification.
We apply a qualitative case study of an ECV1 ecosystem in Finland and Sweden.The data are collected using semistructured interviews with transport experts across the ecosystem.The ECV ecosystem refers to the highly complex network of interdependent actors and relationships [14], [22], [23] in which various participants and institutional players, including vehicle manufacturers, logistics companies, charging infrastructure providers, and policymakers, interact to form a unique and innovative value proposition [3], [24], [25] for the growth of ECVs.
This study contributes to the assessment of BM performance by proposing an assessment framework for BM performance, employing scalability and replicability as performance indicators.It develops a set of qualitative and operational determinants of scalable and replicable BMs, categorized in three groups: technical; economic (or business-oriented); and regulatory.It also illuminates both concepts by providing a conceptual clarification of scalability and replicability and highlighting their possible interconnection.It also contributes to the emerging literature on BMs by expanding its boundaries from the single firm to the ecosystem.Applying an ecosystemic approach to this context is relevant because the ECV ecosystem comprises a wide range of stakeholders and institutional players from multiple industries such as freight transport, the auto industry, and energy systems.Finally, the article addresses practical implications for managers in considering scalability and replicability when designing new BMs.
The remainder of this article is structured as follows.Section II addresses the theoretical background.Section III presents the research method, including the collection and analysis of the data.Section IV presents the findings.Section V discusses the key results, concluding with implications for future research.

II. THEORETICAL BACKGROUND
This section presents a theoretical background for the study.It first presents a concise overview of the BM literature.A review of BM performance follows.Finally, the section explores two proposed performance indicators of BMs: scalability and replicability.

A. Business Model Concept
In recent years, BMs have become increasingly popular among practitioners and scholars as a tool for describing new ways of doing business [3], [24], [25].Although the literature has viewed BMs in several ways [26], [27], scholars seem to agree that BMs act as blueprints, defining how the company operates in the market, and how it creates value [2], [3], [28], [29].Some authors have addressed BM as a firm-centric yet boundary-spanning unit of analysis [24], [30].Zott et al. [24] state that BMs are established as a new unit of analysis, nested between a single company and ecosystem 2 levels.They claim BM can be used from a holistic perspective to analyze how firms conduct business by referring to the focal firm's activity system [3], [10], [31].In this article, we adopt the BM definition by Zott et al. [24], who articulate BM as "a system of interdependent activities that go beyond the boundaries of the focal firm and involve its partners" [24, p. 216].
There has recently been a shift in the focus of BM thinking from the initial stream, which aimed to define "what business models are," to a second stream that responds to the question of "what business models are for" [32], [33].This shift reflects growing interest in BMs' practical applications [30].In the first stream, scholars explore decision-making by perceiving BM as a descriptive tool for showing the connection between elements [33], [34].
In contrast, the second stream considers the BM as an explanatory vehicle for exploring new opportunities and researching futures [25], [35], [36].This new stream brings a different use of the BM as a means to explain relationships between events and show causality [37], [38], [39].In this stream, the BM helps answer questions about what firms offer their customers regarding products/services and value propositions, how and where they do this, and why and how firms do business profitably [4], [10], [40].
The initial step toward the latter research stream was presented by Casacesus-Masanell and Ricart [2] and Baden-Fuller and Morgan [41], who described BMs in terms of choices and their resulting outcomes (consequences).Outcomes are tangible, emerging due to the structural and strategic choices made at the managerial level within a BM [42].The extant BM literature identifies several outcomes such as scalability and replicability expected to be present in a successful BM [43].This means the 2 Business ecosystems have recently emerged as a highly complex form of interfirm collaboration.While BMs center on a focal firm's approach to creating and capturing value, ecosystem perspectives provide a broader view of collaborative efforts in value creation and capture [114].These ecosystems represent highly complex joint value initiatives among firms that remain interdependent despite loosely coupled connections.Such ecosystems enable focal firms to deliver value to customers beyond their standalone capabilities, emphasizing a shared reliance on the resources and expertise of other ecosystem participants [115], [116], [117].It is noteworthy that this business ecosystem interdependence is particularly high relative to other community constructs in management, such as fields, industries, and supply chains, due to the more loosely connected nature of associations [118].
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BM has inherent characteristics, strategies, or choices that lead to such outcomes 3 [44].

B. Business Model Performance
Performance is generally defined as "how well a thing does a piece of work or an activity" [45].Concerning business, performance pertains to "how successful a BM is or how well or badly it works" [46].It is at the heart of any organization.Performance refers to the efficiency and effectiveness with which a firm executes its activities [47].This concept serves as a critical enabler in achieving a firm's strategic goals [48].The recent BM literature does not focus on performance as a specific research theme.However, BM performance has recently gained attention from scholars, as it has been identified as a critical factor for businesses of all sizes and sectors, contributing to their success or failure.Research on BM performance has stemmed from strategic management discussions of BMs [26], [39], [49].Malone [50] was among the first to investigate whether some BMs performed better than others.By examining various BMs, he concluded that customer-focused BMs perform better than those focusing on products.
The existing research on performance suggests a positive relationship between performance and business model innovation (BMI) [19], [51].BMI has been defined as "designed, novel, nontrivial changes to the key elements of a firm's BM and/or the architecture linking these elements" [34], [52], [53].Aspara et al. [19] compared financial performance implications between BMI 4 and replication.BMI refers to the creation of a new BM differing from existing ones; BM replication refers to the replication of successful aspects of a firm's BM for new customer segments or business contexts.Cucculelli and Bettinelli [54] suggested that intangible assets such as intellectual property and knowledge management played a significant role in driving the performance benefits of corporate entrepreneurship.Karimi and Walter [55] examined the adoption and performance 3 To exemplify further, consider the example of a leading EV manufacturer that will commence production of solid-state battery prototypes [119].Understanding the growing demand for EVs and foreseeing potential supply chain disruptions, the company's managerial team makes a pivotal decision.They choose to invest in vertically integrated operations.This means that instead of relying on numerous external suppliers for battery technology-one of the most critical and expensive components of an EV-they opt to develop and produce their own batteries.This choice, embedded within their BM, has several distinct features geared for scalability.First, controlling battery production ensures a steady supply for their increasing vehicle production needs.Second, in-house battery development means they can continually innovate, improving efficiency and reducing costs.This will cater not only to their current vehicle models but also future ones.Furthermore, in-house battery production allows the company to offer energy solutions beyond just vehicles, expanding into home and industrial energy storage solutions, thus broadening its market reach.This move also positions them to quickly scale their production up or down based on the demand not only for their vehicles but for the broader clean energy market.In essence, the scalability this EV manufacturer witnesses is not a coincidence.It is an "outcome" of their BM, which is crafted on the managerial team's choices.Their decision to embrace vertical integration and the resultant scalability it provides testifies to how managerial choices, when aligned with industry foresight, can lead to BMs that are not only innovative but inherently scalable. 4Although there is a robust body of literature on BMI, our study does not focus on BMI.Instead, it addresses BM change, which concerns modifying how a company creates, delivers, and captures value in response to internal or external factors such as technological innovation or changes in the business environment [120], [121].
of disruptive BMI, stating that companies adopting disruptive BMs outperformed their competitors' revenue growth and profitability.Clauss [8] addressed the mediating role of BMI in the relationship between firm-level strategic agility and firm performance.They challenged conventional beliefs, suggesting that although value proposition and value creation of BMIs were positively correlated with firm performance, value capture of BMI was negatively related to firm performance.In parallel, Moradi et al. [45] mentioned the positive effect of BMI and open innovation on performance.Latifi et al. [56] studied the relationship between BMI and performance in European small and medium-sized enterprises.They stated that factors like efficiency, revenue growth, and organizational capabilities influenced the relationship between BMI and the company's overall performance.Menter et al. [57] also studied the relationship between BMI and its impact on firm performance over time.Their results elucidated a positive, if delayed, impact of BMI on firm performance, highlighting the importance of planning BMI activities and resource allocation at the strategic management level.
The measurement of BM performance has also sparked scientific debate [8], [34].Performance measurement offers insight into the alignment and execution of strategic plans at various organizational levels [47].Kaplan and Norton [58] underscored the importance of performance metrics in conveying management's priorities across the firm, thereby guiding and focusing efforts on future organizational advances.The performance of BMs has often been measured by the BM's features, themes, variable levels, and outcomes (e.g., [49]).Heikkilä et al. [59] compiled an extensive open repository of diverse metrics associated with BM elements and performance, representing a wide range of perspectives.Batocchio et al. [60] proposed a method for assessing the performance of BMs using experimentation.They highlighted the need for a systematic and structured approach to assessing the performance of new BMs.Bouwman et al. [61] examined the relationship between digitalization, BMs, and performance, stating that companies could improve their performance by adopting innovative BMs adapted to the digital environment.They identified several key factors influencing the BM's success, including involving employees, using external networks, and the availability of financial resources.Zia et al. [62] discussed the importance of digital dynamic capabilities on the BM performance of B2B distribution firms.They explored how the development of transformation capabilities can help firms transform their BMs and adapt to the changing market conditions.Kurucz et al. [63] proposed a framework for assessing sustainable BMs focusing on relational leadership practices.The article suggested a set of capabilities and practices such as stakeholder engagement, collaboration, and transparency to develop and assess sustainable BMs.Montemari et al. [64] highlighted the relationship between BMs and the design of performance measurement systems to identify KPIs.Snihur and Bocken [9] characterized the challenge of BM performance by stating that BMI was positively associated with the firm's economic performance, generally assessed based on criteria such as firm revenue growth, return on equity, operating profits, or stock market value.Evers et al. [65] further identified BMI financial performance indicators in international markets, such as revenue growth, profitability, and market share.
Lüdeke-Freund et al. [66] were among the few who argued that traditional approaches to assessing BM performance fell short of capturing BMs' complex and dynamic nature.Such traditional approaches, which are mostly based on financial and strategic perspectives, can sometimes create a skewed perception of BM performance.Instead, the assessment of BMs requires a holistic and multidimensional approach that considers both financial and non-financial aspects, going beyond surface-level metrics and deepening into BMs' inherent strengths and potential vulnerabilities.
Nonfinancial indicators of BMs provide a more holistic understanding of a company's performance and potential for longterm success [65].While financial metrics offer insights into a company's financial position, these nonfinancial indicators can illuminate its strategic positioning, adaptability, and future growth prospects [67].Nonfinancial performance indicators include scalability, replicability, resilience, and viability, as well as innovation and societal impact [65].Such indicators can be used in conjunction with financial metrics to provide a more complete picture of a company's performance and help identify areas for improvement.Despite the burgeoning interest in nonfinancial indicators in performance assessment, the embrace of such indicators remains notably scarce in the BM literature.

C. Business Model Scalability
In the BM literature, scalability has received considerable attention and has been explored in different contexts, including information technology, telecommunication systems, and distributed computing systems [68], [69], [70].Scalability is typically defined as an organization's (or a system such as a computer network) capacity to adjust its size and still perform effectively under increased or growing workloads [17].Stampfl et al. [18] emphasized that a scalable system should be able to preserve or improve its level of performance, even when subjected to growing operational demands.However, there is no widely accepted definition of scalability in the business context.Its common definition is closely tied to a company's growth potential, often characterized by the ability to leverage economies of scale, i.e., unit costs decreasing with increasing production [18], [71].Nielsen and Lund [72] directly linked scalability to the scaling of a business, suggesting that scalability enabled a business to grow.In contrast with earlier perspectives [73], current research does not limit the definition of scalability to growth size [74].For example, Carucci [75] suggested that although growth and scaling pertain to the same phenomenon, scaling was a particular type of growth.He argued that scalability involved the ability to grow without sacrificing efficiency and effectiveness.
Drawing on the existing body of literature on scalability and BMs, the notion of BM scalability can be aligned with the previously defined concept of scaling, which pertains to the organizational growth or enhanced turnover to achieve economic benefits (e.g., through economies of scale in value creation, value delivery, and value capture) [18], [72], [76], [77].Björkdahl and Holmén [78] stated that BM scalability referred to a BM's capacity to augment its revenue faster than the associated costs.
Zhang et al. [79] complemented the older basic definition by stating that "BM scalability indicates the degree to which a BM design can achieve its desired value creation and capture targets when the number of users/customers increases and their needs change without requiring proportionally more resources."Building on BM dynamics, Sanasi [80] highlighted that a BM's scalability was closely related to its ability to adapt to changing market conditions, customer needs, and technological advances.She defined BM scaling as the ability of a BM to attain profitable growth by expanding the new venture's userbase, while maintaining the stability of its remaining features.The scalability of a BM is closely related to its ability to adapt to changing market conditions, customer needs, and technological advances.
A recent research stream has emerged investigating the concept of scalability in the context of new technologies and future BMs by highlighting BM scalability as a critical element for companies to successfully achieve sustainability. 5Juntunen et al. [69] argued that scalable BMs enable the integration of new processes and systems to support growth and change.Ahokangas et al. [4] went a step further, examining scalability challenges in the telecommunications industry.They noted these businesses faced significant challenges in achieving scalability, proposing several scalable BM options to overcome them.Hultberg and Pal [81] explored the scalability of circular economy BMs, noting that these BMs faced various scalability challenges, including low consumer awareness, a lack of product standardization, and limited stakeholder collaboration.To overcome these challenges, Hultberg and Pal [81] proposed several strategies for improving the scalability of circular economy BMs, including the development of standardization and certification programs, promotion of circular economy practices, and creation of collaborative stakeholder networks.
To achieve a detailed understanding of scalability, we reviewed the current literature.The concept of scalability touches on various fields, such as business strategy, engineering, and information and communications technologies.However, Björkdahl and Holmén [78] highlighted the absence of systematic attempts to identify the determinants of scalable BMs.Acknowledging this gap in the literature, some authors have undertaken preliminary research.Stampfl et al. [18] addressed this issue by developing a model to investigate BMs' scalability in companies with internet-based models.Nielsen and Lund [17] created a framework based on empirical research with companies with BMs incorporating scalability determinants.Table I summarizes the determinants of scalability in the reviewed literature. 5Many scholars have explored the relationship between scalability and sustainability in BMs.For example, Bigdeli et al. [122] explored the intersection between BM scalability and sustainability, and Jabłoński [123] discussed the challenges and opportunities for creating scalable and sustainable BMs in organizations.Baldegger [124] examined the interaction between BM sustainability and scalability by stating that businesses must consider both sustainability and scalability when designing BMs.He highlighted the tradeoffs between these two factors, exploring how firms could balance sustainability and scalability by adopting sustainable practices and creating new revenue streams.It is noteworthy here that although several studies [43], [91], [125] recognized scalability, replicability, and sustainability as three outcomes expected from a successful BM to be present, this article focuses on scalability and replicability.
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D. Business Model Replicability
While scalability refers to the possibility of growth [18], replicability refers mostly to the possibility of transferring to other contexts.Replicability refers to the ability to reproduce results from a scientific study or research experiment [87].In the context of business and management, replicability has been defined as the ability to duplicate the success of a BM or strategy in different contexts or situations [19].It refers to the generalizability of a BM or strategy.Replicability enables firms to scale their operations and achieve growth by replicating their BMs in new markets or industries.Winter and Szulanski [88] were among the first to explore the concept of replicability, emphasizing that significant growth often required exploitation in the form of replication to maximize value.They expanded on this by examining replicability in a broader context, arguing that replication was a key strategy for firms looking to achieve growth and scale their operations.They highlighted replication as an effective strategy for firms, as it allowed them to leverage the success of existing BMs and reduced the risks associated with innovation.Replicability can also lead to increased payoffs in learning curve benefits for the firm, as well as increased speed to new markets and lower complexity in implementation [65].However, a firm's sustained survival and success rely on its ability to adapt its BM in accordance with the external business environment [19].
The research on replicability of BMs has been little discussed [88].BMs' replicability pertains to the process of the innovative firm gaining knowledge and refining its new BM by selecting the essential components for its duplication in suitable geographic locations, creating abilities to transfer knowledge regularly and preserving the model's operation after its replication [19], [88].Dunford et al. [20] provided a practical example of BM replication in action.They examined how a company used BM replication to achieve early and rapid internationalization.They stated that BM replication could be a successful strategy for companies wishing to expand into new markets, as it allowed them to leverage existing resources and knowledge.It has also Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.

TABLE II DETERMINANTS OF REPLICABILITY IN THE REVIEWED LITERATURE
been argued that replication does not generally give rise to a firm's productivity and relative performance gains because it works as a "duplicate" of the activities performed by the firm at its current productivity levels, which are then transported to other markets or regions or to gain new customers [89].Dunford et al. [20] also indicated that firms first used BM experimentation in home markets.They then exploited their BM through BM replication on international markets.A case study conducted by Sosna et al. [90] supported this finding: A Spanish retail franchise underwent a trial-and-error phase in its domestic market before pursuing a replication strategy of its BM in foreign markets.Finally, Aspara et al. [19] highlighted the positive relationship between BM replicability and financial performance, suggesting that firms should consider replicability when designing and implementing their BMs.Table II summarizes the determinants of replicability in the reviewed literature.
Despite these delineations, a gap remains in the literature that simultaneously provides a conceptual clarification of both scalability and replicability and underscores their potential interconnection in BMs.While several studies consider scalability and replicability to be the same concept, others claim that, though related, they differ in their core objectives and operational implications [85], [86].Scalability is often linked to an organization's growth potential, specifically the capacity to leverage economies of scale [17].The discourse on scalability transcends mere growth; it also concerns growth without compromising efficiency and effectiveness.Meanwhile, replicability refers to the ability to duplicate or transfer a BM's success to different contexts or situations [20], emphasizing a BM's generalizability and allowing firms to replicate their BM in a new environment.
The BM literature underlines that replicability is not merely about duplication but also about understanding, adapting, and implementing a BM's crucial components for success in various situations.

III. METHODOLOGY
In this section, we describe the study's research method in examining and evaluating BM performance using scalability and replicability as performance indicators.Based on the above discussion, empirical research was conducted to explore qualitative measures to determine BM scalability and replicability in the context of ECVs.To do this, we employed a qualitative methodology combining exploratory research and a single case study analysis of the ECV ecosystem to obtain a rich and in-depth insight into this under-researched area [92], [93].The research topic's complex and exploratory nature and the early stage of transport electrification justify an exploratory study, which allows the authors to explore the determinants of scalable and replicable BMs in the context of ECVs [94], [95], [96].A single case study is a common research method in business research, enabling the expansion and generalization of theories by integrating existing theoretical knowledge with new empirical insights [92].This attribute is fundamental when studying an issue that has not already been extensively researched, as in this research [97].Single case study approach is particularly suitable for responding to process-oriented "how" and "why" questions and examining real-life events [92].This enables the exploration of a phenomenon within its context through the incorporation of diverse data sources [98], and it concerns research with the case designated for a certain purpose.

A. Research Design
This article adopts a two-step research design to identify the determinants of scalability and replicability, including 1) extracting determinants of scalability and replicability, and 2) categorizing determinants as technical, economic, and regulatory.In the first step, we extensively collect primary and secondary data sources relevant to ECV BMs.We extract key determinants that influence scalability and replicability of BMs.These determinants not only define a BM's scalability and replicability but also elucidate the structural and functional aspects that facilitate or hinder their scaling up and replication.
In the second step, we categorize the determinants of scalability and replicability in three primary groups: technical; economic (or business-oriented); and regulatory.This is rooted in the BM literature [99], [100], [101], which traditionally emphasizes these external aspects as pivotal in the assessment of a BM's potential for scaling and replication.Technical determinants acting as enablers of scaling and replication allow the evaluation of a BM's inherent capacity for scaling and replication, and assessing its feasibility for scaling up and/or replication [18], [101].Economic (business) determinants offer a financial lens, examining the viability of pursuing scaling up or replication, involving crucial steps like cost-effectiveness, revenue stream diversification, and optimized resource allocation, and examining BMs' adaptability on a larger scale or in a different context than the original case [18], [71].Finally, regulatory determinants play a pivotal role by allowing, delimiting, or protecting/safeguarding a certain BM [99].They involve navigating and complying with legal frameworks, industry standards, and government policies, ensuring the BM's scalability and replicability in different regulatory environments.
The rationale behind this three-fold categorization is grounded in BMs' multifaceted nature and the factors influencing their performance.The technical aspect highlights the BM's operational capabilities, integrating with current systems and scaling/replicating with demand [18].The economic aspect examines the BM's profitability and financial robustness in revenue generation, cost control, and maintaining a competitive advantage [18], [71], [72].Regulatory aspects pertain to compliance with laws and regulations, acknowledging that a BM's performance depends on its ability to navigate and adapt to the legal frameworks governing business practices [102].Together, these aspects offer a more holistic approach to evaluating BM performance.This holistic categorization underscores the interconnectedness of these determinants, as a firm's ability to scale or replicate in the real world is seldom influenced by one aspect alone.Instead, the integration of technical capabilities, economic feasibility, and regulatory alignment comprehensively determines a BM's performance in different contexts.

B. Data Collection
Data were collected from two sources: secondary sources and semi-structured interviews [103].Twenty-six semi-structured interviews were conducted with transport experts (see Table III), with the primary objective of achieving an adequate level of data saturation [104].The interview sampling process was mainly purposeful sampling to select information-rich respondents, followed by snowball sampling [95], [105].We initiated the process of identifying prospective respondents with a thorough search for companies that specifically focused on ECVs.We then asked the respondents about other relevant actors within the field.The respondents were selected based on their knowledge of transport and ECVs, as well as their strategic insight into fleet electrification.When contacting each company, we described our research and asked for the most appropriate respondents.Respondents were therefore randomly sampled in close collaboration with the companies.Our respondents were management-level experts on fleet electrification within their respective companies in Finland, Sweden, and Poland, 6 To ensure our respondents' diversity, we aimed for an assortment of participants from various companies within the ECV ecosystem.The companies represented various ecosystem actors in the ECV development and implementation, ranging from vehicle manufacturers to infrastructure providers and policy advocates.This diverse selection revealed a reasonable variance level, enriching our understanding of complexities of our case, and resulting in the strengthening of the generalizability of our findings.
All interviews followed a semi-structured thematic guideline.An interview guide focused on background information about the respondent, company, business activities, and future considerations.The interview guide comprised open-ended questions, allowing for flexibility and follow-up during interviews.To elucidate scalability and replicability of BMs, the interview guide was enriched with probing questions about challenges, strategies, and factors that influenced the scalability and replicability of ECV BMs.These tailored questions were designed to delve more deeply into the topic's intricacies, illuminating the nuances and underlying determinants that indicated scalability and replicability.This questioning allowed us to derive meaningful insights directly related to the core objective of understanding BM scalability and replicability.The interviews were conducted through online video calls from 2020 to 2023, each lasting between one and two hours.All interviews were recorded and transcribed.
To verify and reinforce the data gathered through interviews, we drew on credible secondary sources, consisting of reputable sources such as research papers, business case studies, and scholarly conferences, as well as, to some extent, the grey literature (e.g., company releases) and news and press releases, as this emerging research stream is in its early development.These sources played an essential role in triangulating the data and confirming or refuting the findings obtained through the interviews [106].They gave a concise insight and comprehensive information about what is occurring in the Finnish and Swedish contexts.All sources are also considered relevant for verifying the consistency and discrepancy of evidence, which is a critical step in the subsequent data analysis.

C. Data Analysis
We employed qualitative thematic analysis to identify the scalability and replicability determinants influencing BMs' ability to successfully scale up and be replicated in different contexts.Qualitative thematic analysis is widely used in social sciences for analyzing qualitative data.It involves a systematic and iterative process of discerning, examining, and presenting patterns or themes within a dataset [104], [107].This method allows a deep exploration of the data, providing rich and detailed insights into the research question or investigated phenomenon.However, given the limited previous research on the performance of BMs, we were careful to avoid forcing data into predetermined theoretical classifications.Instead, we let initial codes and themes emerge naturally without squeezing data [108].The qualitative thematic analysis involved two phases.The first was designed to facilitate familiarization with the data, in which the dataset and interview transcripts were repeatedly scrutinized to gain a holistic understanding of the context [109].
In the second phase, the data were coded based on Saldana's [110] codes, categories, and concepts frame.This method is a systematic data analysis approach that explores and interprets emerging themes.Saldana's method involves a three-step process.It begins with coding, where the data are segmented into smaller units based on recurring patterns or themes.The process of coding allows the consolidation of data for meaning and explanation [111], as the codes serve as labels or tags to identify and organize the data.For this step, we used both a priori codes from theory (i.e., growth, local adaptation, and localization) and codes from data (i.e., centralized platforms, standardization, and partnership agreements). 7The literature-derived codes guided the coding procedure and ensured a connection to prior research while permitting flexibility in incorporating codes from data [112].At this stage, the Nvivo software package was used to code the data and record memos about the data and themes.After transcribing and extracting the codes, we closely examined the interviews to identify potential new themes emerging from our discussions with respondents.
The next step of Saldana's method [110] is the categorization of related codes in grouped.This helps establish structure and organization within the data.The last step is conceptualization, in which the categories are further examined and analyzed to identify broader concepts or themes emerging from the data.This facilitates a comprehensive and in-depth data analysis, allowing researchers to uncover meaningful insights and draw conclusions based on the patterns and relationships identified within the coded and categorized data.
We were aware that qualitative thematic analysis could often be susceptible to biases from subjective interpretations, so we undertook several rigorous steps to ensure the findings' credibility and transferability.To ensure credibility, we employed respondent-checking, in which interviewees were provided with a draft of our paper to validate accuracy of our understanding.This iterative process ensured our thematic analysis resonated authentically with the respondents' knowledge.Additionally, to enhance transferability, we provided rich and detailed descriptions of the research context and the participants' backgrounds.This meticulous detailing allows future researchers to determine the extent to which our findings may be applicable to other settings or contexts.Furthermore, we ensured the reproducibility and openness of the research design through comprehensive documentation.The process of selecting key respondents was carefully executed, and the interview data underwent thorough transcription and validation, ensuring robust internal validity and reliability.

IV. FINDINGS
This section presents a conceptual framework of two performance indicators for the BM: scalability and replicability.The framework includes qualitative and operational determinants that make ECV BMs scalable and replicable.These determinants are presented as they emerged from the data, starting with determinants of scalable BMs in the context of ECV, followed by determinants of replicable BMs.

A. Determinants of Scalability in ECV Business Models
Our findings highlighted the pivotal role of scalability in the emerging ECV ecosystem.As the transition to electrification gains momentum, companies must ensure that their BMs can handle surging demand and the challenges of rapid growth.This involves not only the capacity to increase production volumes but also the agility to maneuver through market uncertainties, infrastructural developments, and technological advances.Analyzing the key determinants of scalability reveals a multifaceted approach encompassing technical, economic, and regulatory dimensions (see Table IV).These dimensions collectively define the readiness and capacity of BMs to grow and adapt within a rapidly evolving ecosystem.

1) Technical Determinants:
The key technical determinants are associated with infrastructure development and management, technological advancements and integration, operational efficiency and flexibility, resource and energy management, and market responsiveness.The determinants primarily concern the tangible infrastructure and systems required to support the scaling of ECV operations.The local development of infrastructure, including the placement of charging stations and maintenance facilities, is foundational to accommodate the technical requirements of ECVs, such as high computational capacity for processing transactions.Integrating such computational capabilities empowers businesses to process large transactions securely Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.

TABLE IV DETERMINANTS OF SCALABILITY IN ECV BUSINESS MODELS
and navigate the complex energy landscape effectively.The management of system-level information is another determinant of scalable BMs, which is critical in enabling businesses to make informed decisions and respond proactively to market dynamics.R&D investment is the cornerstone of scalability, enabling improvements in vehicle range and charging time efficiencies-both critical for widespread adoption.Operational flexibility, system-level information management, and grid flexibility provide the backbone for scaling operations, ensuring the BM can adapt and respond to fluctuating market demands and technological advances.The inclusion of scalable battery recycling solutions and development of a modular and integrated charging infrastructure further underscore the need for forwardthinking resource management and system design that address material shortages and support mass-market adoption.As the CEO of the energy equipment and solutions company stated, "Currently, the size of a single electricity storage unit can serve most applications quite well.However, as we design modular units, if the project wants to expand and install multiple units, we can easily connect multiple energy storage units in series, so we get higher capacity and power to address the current bottleneck with growth capability and scaling up." Additionally, pooling resources allows ECV businesses to achieve the necessary scale to attract investors and support their growth trajectory, exemplified by virtual power plants and aggregating distributed energy resources.Grid operators' proactive involvement is essential for future-proofing the infrastructure, ensuring it can cope with the scaling demands of ECV adoption.Infrastructure and ECV development must proceed in tandem to avoid bottlenecks, ensuring grid readiness to meet a fully electrified commercial fleet's power demand.Integrating software with hardware and empowering grid operators ensure that infrastructure development keeps pace with vehicle advances, with renewable energy integration further bolstering the model's scalability.These technical determinants collectively establish the groundwork for scalable ECV BMs to thrive.
2) Economic Determinants: Economic determinants are associated with strategic planning and ecosystem adaptation, collaboration and partnership, financial management and investment, revenue models and pricing strategies, operational efficiency and cost management, and resource optimization.They address the strategic and financial underpinnings necessary for scalable growth.Scalable BMs rely on regularly updated strategic plans that acknowledge the constantly changing nature of the emerging ecosystem.This enables businesses to anticipate market shifts, identify emerging trends, and adjust their strategies accordingly.As the senior product manager of the motor vehicle manufacturing company stated, "If you think about ten years ago, truck companies made their strategies every five years.But now, they've basically been changing their strategies every year.So, I'm trying to keep my eyes on the horizon five years ahead and even more."Collaboration with partners and pooling resources demonstrate the power of synergy in overcoming macrobarriers to scalability, such as investment constraints and market entry challenges.Forging strategic partnerships also helps businesses leverage their collaborators' expertise, networks, and resources to overcome regulatory hurdles and create favorable growth conditions.Engaging with consortia and embracing alternative revenue models reflect a nuanced understanding of the value chain and customer segmentation.Pooling resources in virtual power plants attracts investors and supports scalability.Alternative revenue and pricing models introduce flexibility and market adaptability.Moreover, addressing the economy of scale in strategic planning and subsidiary management assists cost reduction and operational efficiency maximization.The economic determinants underscore the critical need for robust financing and resource management strategies and collaborations that underpin scalability.
3) Regulatory Determinants: Regulatory determinants encapsulate the legal and policy frameworks that enable or hinder the scalable growth of ECV BMs.For example, charging level standards are fundamental to ensuring interoperability and ease of use across different jurisdictions, facilitating market expansion.As the program director of the innovation company emphasized, "It's beneficial to have widely used charging standardisation in place.Such a standard not only concerns the

technical part of charging vehicles but the operational level, such as following the utilisation rate and energy consumption.
Standards also enable building the data-driven basis on top of the physical infrastructure."Clear and consistent regulations create a stable environment for attracting investment and encouraging businesses to scale their operations.Navigating this landscape requires businesses to be proactive in regulatory engagement and compliance, with a keen eye on future developments that may impact scalability.
In conclusion, the successful scaling of ECV BMs necessitates a comprehensive approach integrating technical innovation, economic viability, and regulatory foresight.These three aspects-technical, economic, and regulatory-must be addressed in harmony to ensure that ECV BMs can expand and are resilient to the challenges the market's rapid transformation presents.Scalability thus serves as a robust performance indicator, with these determinants providing a blueprint for growth and long-term competitiveness in the ECV ecosystem.

B. Determinants of Replicability in ECV Business Models
In the ECV landscape, replicability becomes crucial as transport electrification presents diverse challenges and opportunities across various geographies.A replicable BM allows firms to enter new locations with fewer modifications, mitigating risks and reducing the lead time for market penetration.Moreover, as regulations, consumer preferences, and infrastructural readiness vary across regions, a replicable ECV BM ensures firms can maintain consistency in their value proposition, adapting only the nuances that cater to specific regional demands.Replicability thus enhances companies' versatility and flexibility in the expanding and diverse ECV ecosystem.Replicable BMs in the context of ECVs encompass distinct determinants that facilitate their repeatability across different geographical locations (see Table V).Such determinants are divided into technical, economic, and regulatory groups: 1) Technical Determinants: Centralized coordination is one of the foundational determinants of BMs' replicability, offering a harmonized approach and streamlining operations.Producing various models of ECVs to address various customers' needs emphasizes the significance of market segmentation, ensuring a broader reach and market appeal, thus promoting replicability.Furthermore, interoperability between key actors-between port authorities and charging operators, for example-is crucial, ensuring smooth transactions and operations within the ecosystem.The emphasis on the charging network's development signifies the importance of infrastructure that supports seamless operation of ECVs.Energy roaming signifies a unified energy network, facilitating cross-border energy exchanges, and ensuring consistent energy supply, irrespective of geographical distinctions.As the director of logistics strategy at the Transportation Tech company highlighted, "Currently, we have challenges in gaining access to the charger when we're driving in a new country.Maybe we need roaming energy BM to sell electricity as in roaming cellular services so we can buy electricity from whoever we want, regardless of who owns the facility, and who their supplier is." 2) Economic Determinants: Clear pricing models and defined energy prices in different countries help businesses provide predictability and confidence to stakeholders, reducing entry barriers in new markets.Adjusting BMs to resonate with geographical locations allows businesses to remain contextually relevant and mitigate regional challenges.As the managing director of the ECV manufacturer noted, "We have different BMs for different countries based on what customers want.We adjust our BMs to different solutions.For example, we have countries where leasing is very popular, and 80% of trucks are sold with finance leasing; we also have countries where only 30% are financed."Another key determinant of replicable BMs is Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.
standardization, which dictates a uniform approach to operations, product offerings, and service delivery.Standardization ensures consistency across different markets or regions, helping BMs replicate in a new market with minimal adjustment.However, the pursuit of standardization, though promising uniformity and simplicity, comes at a tangible financial cost.Companies need to weigh the benefits of standardized architecture against its inherent economic implications.
3) Regulatory Determinants: The integration and harmonization of policies across local, national, and EU levels play a pivotal role in defining the trajectory of ECV BMs.Updated regulations, especially those accommodating autonomous ECVs, reflect a forward-looking approach, anticipating future trends and innovations.While uniform technical standards simplify operations, they must be juxtaposed with individual country standards to ensure compliance.The emphasis on standards such as OCCP for operation, IEC CIM for smart grids, and standardized EU grid codes underscores the drive for a unified operational landscape.As the CEO of the energy equipment and solutions company noted, "Different regulations exist in different countries regarding grid code compliance and standardisation.So obviously, whenever we expand our business to another country, even within the European Union, we must ensure the product and BM comply with local regulations." The replicability of ECV BMs is therefore fundamentally linked to the synergy between technical feasibility, economic viability, and regulatory alignment.Technical determinants lay the groundwork for operational replication; economic determinants ensure financial sustainability; regulatory determinants provide a consistent legal framework for BM application.When these determinants are addressed collectively, they form a robust foundation for replicable BMs that can be applied across various contexts, ensuring adaptability and long-term success in the ECV ecosystem.

A. Theoretical Contributions
Our study focused on assessing BM performance in the ECV ecosystem, using scalability and replicability as performance indicators.Interpreting our findings on assessing BM performance provides valuable insights, offering a robust framework for businesses operating within the ecosystem.This study's significance is further amplified by its comprehensive approach to integrating multiple determinants of BM performance, encompassing technical, economic, and regulatory factors.This holistic perspective provides a more nuanced understanding of scalability and replicability than previous studies, which may have focused on isolated aspects of business performance.Integrating these determinants delivers a multidimensional view that is particularly relevant for the ECV ecosystem.
Our study is aligned with the existing literature [17], [18], [19], [20], [21] emphasizing scalability and replicability in sustainable growth and success.These determinants not only characterize BMs' scalability and replicability but illuminate the structural and operational elements that either support or impede scaling up and replicating BMs.Previous studies have emphasized technical determinants in the scalability of BMs, particularly in the context of infrastructure development [18].The current findings are aligned with this in highlighting the necessity for infrastructure, computational capabilities, and flexible operations management.Consistent with previous research [3], strategic planning and resource pooling have been identified as vital for BMs' scalability.The importance of partnerships and strategic alliances is also a recurring theme in the existing literature [70], [83], [85], [113], which the current research supports.
Similarly, replicable BMs' determinants are aligned with the literature emphasizing the role of centralized coordination [86] and geographical/contextual adaptation [20].The findings also underscore the need for a harmonized approach and interoperability, particularly in technology-driven sectors [85].The emphasis on standardization is also well supported by the literature that discusses the benefits of a unified environment for cross-border business operations [91].
However, our study deviates from some prior research in several areas.The current research may emphasize modular infrastructure and the integration of software and hardware solutions more than the past literature, recognizing the rapid pace of technological advances in the field.Unlike some previous studies, which may have underplayed the role of dynamic strategic plans and alternative BMs, the current findings highlight their critical importance in responding to the emerging nature of the ECV ecosystem.There may be a divergence in how proactive engagement with regulatory bodies is viewed; although past research may suggest a more reactive approach, the current findings stress a proactive stance in shaping and responding to regulations.This deviation may be attributed to our methodological approach or the specificity of the ECV ecosystem compared to those examined in the earlier literature.
This study thus contributes to the ongoing discussion of BMs by conceptually clarifying scalability and replicability and highlighting their possible interconnection.Our case indicated that both scalability and replicability were related to BMs' performance, providing an approach for envisioning alternative BMs in the ECV context.Some scholars consider scalability and replicability synonyms that differ partly in meaning; however, our data revealed that scalability and replicability in BMs are two distinct but interrelated concepts that have different implications for a company's success.Scalability is commonly linked to internal flexibility, exhibiting flexibility within its own operations.Yet, replicability is typically connected with a business's external flexibility, involving its capacity to adapt to different external factors and conditions (see Fig. 1).
Scalability is often closely associated with internal flexibility, as it focuses on a BM's ability to adapt and respond to internal factors such as resource allocation, operational efficiency, productivity, and market dynamics, while maintaining its core strengths and advantages.It involves optimizing internal processes, systems, and capabilities to handle increased demand or changing market conditions.Through strategic planning and investing in scalable resources, businesses can adjust their operations, scale up or down, and seize growth opportunities while maintaining operational effectiveness.Internal flexibility enables businesses to efficiently allocate resources, streamline processes, and optimize their operations, ensuring they can meet customer demands and remain competitive in dynamic markets.
In contrast, replicability is often closely associated with external flexibility, as it emphasizes a BM's adaptability to external factors such as geographical variations, market contexts, and regulatory frameworks.Replicability requires businesses to understand and navigate diverse local conditions, cultural preferences, legal requirements, and technical standards.Businesses can replicate their advantages in different markets by adjusting their BMs to suit specific locations and leveraging standardization while accommodating variations in consumer preferences, market dynamics, and regulatory environments.External flexibility enables businesses to tailor their operations, products, and services to local market needs, effectively penetrate new markets, and establish a strong presence in different regions.
Scalability is considered a prerequisite for Replicability in business models: Without achieving scalability, the BM's successful replication becomes challenging or even unattainable, as scalability allows it to be replicated across different contexts and markets without compromising its growth potential and internal flexibility.A scalable BM enables firms to capitalize on economies of scale by optimizing their production, distribution, and marketing processes, resulting in higher profits and market share.A scalable BM can therefore adapt to changing business conditions, customer needs, and technological advances, facilitating replication in different locations or industries.In contrast, replicability refers to a BM's ability to adapt and be successful in different contexts and markets, focusing on its external flexibility.A replicable BM can be applied across different contexts, enabling a company to enter new markets, expand its market share, and grow its business.Without scalability, however, the replication of a BM can lead to a loss of flexibility and growth potential, which may hinder its success in new contexts.Scalability is therefore a prerequisite for replicable BMs.For example, if a company has a BM that depends greatly on a specific set of resources or infrastructure, it may be difficult to replicate this model in a different location where those resources are unavailable, or infrastructure differs.Scalability is therefore a prerequisite that must be fulfilled for replicability to be effectively implemented.A scalable BM provides the foundation on which replicability can be built, as it allows the necessary adjustments and modifications to be made to successfully adapt to different contexts.Scalability and replicability thus work together to create a strong and adaptable BM that can effectively operate in various environments.A BM's ability to be scalable and replicable is ultimately key to its success and sustainability.
Our findings underline that scalability and replicability are more than just buzzwords or aspirations.They become paramount in the ECV ecosystem, as rapid technological advances and evolving regulatory landscapes in this ecosystem demand BMs that can be efficiently scaled and replicated across various geographical conditions.The assessment of ECV BMs using these indicators offers critical insights into the readiness of businesses to capitalize on emerging market opportunities and navigate anticipated challenges.Furthermore, an in-depth exploration of ECV BMs unearths determinants of scalable and replicable BM that other firms might adopt.These determinants can offer invaluable guidance to both newcomers and established firms seeking growth.

B. Managerial Implications
This article offers valuable insights for managers in the ECV ecosystem by emphasizing scalability and replicability as KPIs for evaluating the success of a BM.The determinants of scalable and replicable BMs can help managers make informed decisions when developing and evaluating their BMs.For instance, in the case of scalability, managers in the ECV industry might focus on modular design and infrastructure development, allowing for easier expansion and adaptation as market demands evolve.The findings can guide managers to focus on designing scalable and replicable BMs.Managers can also use the determinants identified in the article to evaluate the scalability and replicability of their BMs and make necessary adjustments to enhance their performance.Considering these determinants helps managers improve the long-term viability of their businesses, attract investors and partners, and increase their chances of success.For example, in improving scalability, a manager might streamline supply chain processes or integrate advanced data analytics for better demand forecasting.
The study provides invaluable insights for managers in navigating the complex interplay of expanding their operations while ensuring their BMs are sufficiently versatile to be replicated in diverse locations.A practical example of this might be a company expanding its charging infrastructure while ensuring the technology and services are adaptable to different regional power grids and consumer behavior patterns.For business leaders focusing on scalability, the pathway is to discern growth opportunities where upscaling can be accomplished, without compromising services' integrity and quality.Managers should seek operational efficiency enhancement through innovative process improvements, cloud-based solutions, and agile workforce strategies, allowing them to cater cost-effectively to increasing demand.Investment in scalable infrastructure, particularly in the ECV sector, should be forward-looking and ready to support a growing ECV fleet.Furthermore, fostering a culture of agility and flexibility in BMs will serve companies well in coping with the uncertainties of rapidly fluctuating conditions.
Turning to replicability, managers must keenly understand geographical differences and their implications for BMs' replicability.Pursuing replicability is most advantageous when models can be standardized across varying regions with minimal alterations.For example, a manager might develop a standardized EV model that can be easily adapted to different regulatory environments and consumer preferences.Mechanisms for seamless knowledge and best practice transfer are fundamental, ensuring success in one part can be emulated in another.
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Compliance with international standards and regulations enhances BMs' interoperability, making replication across borders less challenging.Tailoring BMs to local conditions is also vital for replicability.While maintaining the core value proposition, managers must adapt offerings and forge local partnerships to ensure market relevance and regulatory compliance.
The decision to scale or replicate should be made after a thorough analysis of ecosystem readiness, regulatory landscapes, and infrastructural provisions, and an assessment of local adaptability.Scaling is suitable for scenarios with clear market demand that can be satisfied within the existing business framework.Yet, replicability should be the strategy of choice when venturing into markets characterized by distinct and varied requirements.Scaling may be appropriate in case of expanding the fleet size in a region with established acceptance.Conversely, replicability is preferable for entering a new country with different charging standards or consumer preferences, necessitating tailored adaptations to the BM.In conclusion, leveraging the dual concepts of scalability and replicability help business leaders in the ECV ecosystem to secure sustained growth and maintain a competitive edge in the emerging ECV ecosystem.

C. Policy Implications
This study points to several policy implications for policymakers to facilitate the transition to ECVs.As discussed, the integration of ECVs is facing notable challenges such as scaling the necessary infrastructure, interoperability, and compatibility issues.Policymakers are frustrated by the slow progress and are concerned about the current policy landscape, and whether it has the required scalability and replicability.In this context, our research findings suggest policymakers should not only focus on sustainable solutions but consider the scalability and replicability of such solutions.Policymakers should therefore consider revising existing policies and regulations to incorporate scalability and replicability as essential factors in promoting the implementation of ECVs.
Policymakers can facilitate the transition to ECVs by providing financial incentives, establishing clear standards and regulations, encouraging collaboration, and investing in research and development.They can help ensure the transition to EVs is smooth and successful by working to establish clear standards and regulations for EV charging infrastructure.This includes standards for charging speeds, connector types, and payment systems.By establishing consistent standards, policymakers can promote interoperability between different charging networks, reducing costs and improving convenience for EV users.

D. Limitations and Future Research
This study has some limitations concerning the research method.Single-case qualitative studies are beneficial in gathering data to develop an understanding of a particular research phenomenon.However, replicating the findings in other research contexts can be inherently difficult [92].Qualitative research frequently mentions that limitations offer potential areas for future research.This research also focused on BMs' scalability and replicability, which directed our focus more toward external interactions and dynamics.However, this limited the examination of crucial internal factors within organizations, such as knowledge resources and decision-making structures.The research acknowledges this limitation, suggesting future studies should focus on how these internal organizational resources affect BM performance.
Further research could benefit from a deeper exploration of the synergistic effects between performance and sustainability, as well as their influence on neighboring concepts such as resilience in the context of BMs.Investigating the nexus between these concepts may uncover how an inherently scalable and replicable BM can also be designed to be inherently sustainable and resilient.In-depth studies on the integration of sustainability practices within scalable and replicable BMs can provide insights into balancing economic growth with environmental and social responsibilities.Future research should explore emerging technologies' influence on BM's scalability, assess the impact of regulatory shifts, and examine cross-cultural differences in the replicability of ECV BMs.To further advance the field, research should also focus on developing quantitative metrics that can accurately measure and predict performance of BMs in terms of their scalability and replicability.Such metrics could include KPIs tailored to scalability and replicability, assessing factors like market penetration rate, operational flexibility, and speed of adaptation to new markets.Additionally, assessing BM performance is also critical in identifying and mitigating the risks of crisis-driven business failure.Future research can provide valuable insights into proactive strategies to avoid or manage crisis-driven failure in business operations.Finally, case studies across diverse industries and geographies could be undertaken to test the applicability of these concepts in different contexts.This research could be crucial for identifying industry-specific challenges and opportunities in scaling and replicating BMs while considering the unique requirements of each setting.Comparative analyses of such case studies could lead to the development of a more comprehensive framework, encapsulating scalability and replicability intricacies across various contexts.

TABLE III INTERVIEW
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TABLE V DETERMINANTS
OF REPLICABILITY IN ECV BUSINESS MODELS