Keywords

1 Introduction

Software start-ups are high-tech start-up firms that develop cutting edge software products and/or provide services based on the software they create. The majority of software start-ups are product-based [1]. Software start-ups are a very active component of the start-up market. In 2013, for example, U.S. software start-ups accounted for the largest proportion of new investment (23 %), followed by media companies (16 %), and healthcare services/medical devices and equipment (14 %) [2]. The demand for the products or services of software start-ups is evidenced also by job creation rates almost twice that of the private sector as a whole [3]. The impact of the software industry on economic growth, in general, is reflected in the phrase “software is eating the world” [4].

Despite obvious successes, the failure rate for software firms also is high compared with that of other high-tech industries. Although numerous software start-ups appeared in the marketplace during the Internet bubble of the 1990s, attracting large amounts of venture capital, few of those start-ups survived in the longer term [5]. For example, nearly 80 % of start-up firms failed within their first three years [6].

The objective of this paper is to understand how early-stage software start-ups survive. Early-stage software start-ups refer to software start-ups that are engaged in conceptualizing and developing software products. Understanding early-stage software start-ups is important for two reasons. First, little research has been conducted directly into software start-up survival. An extensive literature on entrepreneurship focuses on explaining the survival of start-ups, in general, where the major emphasis is on manufacturing and therefore on engineering [7, 8]. In contrast, the core elements of the production process in software start-ups are IT skills and IT innovation. To date, IS studies most often examine performance in established firms [9]. The reasons for firm failure are different in new firms and established firms however. For example, established firms often do not succeed because they fail to adapt to changing environment, while the failures of new firms are often attributed to managerial deficiencies of using resources and capabilities [10].

Second, little research has examined the role of management in helping firms survive during the start-up stage of a new software firm. Scholars typically base their investigation of such issues on the resource-based view of the firm, primarily by documenting the resources that lead to effective performance or competitive advantage [11]. The availability of resources is not, however, sufficient to explain why some start-ups survive while others do not. The way in which firms use their resources may explain the variance in firm performance when resources are similar [12]. In other words, management needs to understand how to deploy resources effectively. That is, they need to focus on the actions managers take to manage a firm’s resources thereby creating value for customers and owners [13]. Henceforth, we refer to this phenomenon as “managerial actions.”

Extant resource-based research provides little information regarding the actions managers might best take to facilitate start-up survival and/or competitive advantage [13, 14]. This aspect of RBV is an emerging research stream in management and promises to extend the understanding of the resource-based approach by examining how resources are managed to create business value [13, 15, 16].

We investigate managerial actions that facilitate early-stage software start-up survival. Our paper seeks to address the overall research question: how do resources, capabilities, and managerial actions influence early-stage software start-up performance. Specifically, we view resources and capabilities as the fundamentals that managers draw on to perform managerial actions.

The remainder of the paper proceeds as follows. The next section, Sect. 2, introduces the theoretical background, while Sect. 3 presents the development of the theory of early-stage software start-up survival. We present our conclusions in Sect. 4.

2 Theoretical Background

Because literature on managerial actions grounded in resource based theory, we first review resource based theory (RBT) followed by the research associated with managerial actions.

2.1 Resource Based Theory

RBT focuses on “describing, explaining, and predicting organizational relationships” [11]. Scholars increasingly use the term RBT rather than resource-based view (RBV) due to the fact that “resource-based research has reached a level of precision and sophistication such that it more closely resembles a theory than a view” [11, p. 1303]. Here, we consider first RBV followed by the notion of dynamic capabilities.

From the perspective of RBV, firms invest in valuable, rare, inimitable, and nonsubstitutable (VRIN) resources to gain a competitive advantage [17, 18]. Resources are important in a stable environment. However, in a changing environment, it is not sufficient to consider resources alone. That is, RBV is not applicable in a dynamic environment [19, 20]. Firms therefore need to develop the ability to configure resources to respond to rapidly changing environments [19, 21]; that is, they need to develop dynamic capabilities.

Dynamic capabilities reflect a firm’s ability to modify its resource base, thereby transforming RBV from a static view to one suitable for a changing environment. The core idea of dynamic capabilities is that a firm responds to a changing environment by developing capabilities to extend or modify resources [15]. Such capabilities help a firm to cope with rapid [19], as well as minor changes [15, 19, 21–23]. Although the notion of dynamic capabilities advances the usefulness of RBV in a dynamic environment, it does not explain how resources are deployed or configured to create business value [24].

Within RBT-based research, two important but underdeveloped areas need to be addressed further. First, most of existing literature on RBT does not address the process of resource deployment [11]. Deploying resources and capabilities is as important as possessing those resources and capabilities [25]. The value of resources and capabilities can be realized only when they are deployed effectively [13]. Second, extant literature does not acknowledge the role of management in deploying resources [13, 14]. Apart from performing operational activities such as control or supervision, managers play a prominent role in strategic functions such as integrating complementary resources to develop firm-specific capabilities [15].

2.2 Resource Orchestration

Resource orchestration is a recent stream of research that seeks to understand resource deployment, a vital but under-researched aspect of RBT [11]. Resource orchestration describes “the actions leaders take to facilitate efforts to effectively manage the firm’s resources” [26, p.64]. Managerial actions in resource orchestration take three forms: structuring, bundling, and leveraging. Each category is made up of specific actions. Structuring refers to managing a firm’s resource portfolio that includes both tangible and intangible assets. Structuring includes acquiring, accumulating, and divesting resources. Bundling refers to developing new capabilities and modifying current capabilities. Bundling includes stabilizing, enriching, and pioneering resources. Leveraging refers to using capabilities to compete within the target market or to satisfy customers. Leveraging includes mobilizing, coordinating, and deploying [16].

Effects of managerial actions are contingent on a firm’s external environment. Except for divesting and stabilizing, managers perform such actions when a firm faces high environmental uncertainty. Divesting creates business value only when it sheds a firm’s resources without sacrificing the firm’s current or future competitive advantage [16]. In a highly-uncertain environment, managers are unable to evaluate accurately a resource’s potential for competitive advantage. Therefore, divesting resources may reduce a firm’s potential to create value for customers [16]. Further, stabilizing does not enhance a firm’s competence to maintain its competitive advantage in a highly-uncertain environment. It is easy for competitors to outperform a firm that relies on stabilizing because stabilizing involves making only minor changes to a firm’s current competence [16].

3 Theory Development

In this section, we first introduce the foundations on which our conceptual model is based, followed by the model itself. We then introduce the boundaries of our conceptual model.

3.1 Theoretical Foundations

We first define early-stage software start-up life cycle followed by early-stage software start-up performance. We then present fundamental premises of our conceptual model.

Early-stage Software Start-up. The early stage of a software start-up refers to the period during which a software start-up converts a business idea into a viable solution designed to realize the core functions of the software innovation [27]. First, a start-up faces technical problems associated with software development. Second, there is no structure or formality in such a firm. Rather than a formal organization, a software start-up is likely to be a task group. Entrepreneurs are central to the organization as a whole and they carry out most of tasks.

Early-stage Software Start-up Performance. In this stage, the major focus of a software start-up is software development. Good performance in this stage indicates the potential for first mover advantage. Early-stage software start-up performance can be viewed from both product and process perspectives [28]. From a product perspective, software development performance is reflected in product effectiveness. Product effectiveness refers to the extent to which the prototype fulfils the functional goals of the innovative software product [29]. From a process perspective, software development performance is reflected in process efficiency. Process efficiency refers to the extent to which the software development adheres to an established budget detailing the time and cost of converting an idea to a software prototype [30].

Fundamental Premises. Three premises underlie the development of our conceptual model.

Resources and Capabilities Create Business Value Through Managerial Actions. This premise reflects our belief that (a) resources or capabilities are essential for firms to create business value, and that (b) their effects are realized through managerial actions. Specifically, resources are factors that a firm owns, controls, or has access to, while capabilities relate to deploying resources [31, 32]. Compared with resources, capabilities are unique because they are developed internal to a firm by integrating technical and physical resources [15, 33]. A firm that possesses effective resources and capabilities has the potential to achieve high levels of performance. Such potential is realized when managers take actions to use resources and capabilities effectively [13, 15, 16].

A Software Startup Operates in a Highly Uncertain Environment. A software startup introduces an innovative software product and subsequent innovations to the marketplace. It operates, therefore, in a highly uncertain environment. The high environmental uncertainty of a product-based software startup involves both technical uncertainty and market uncertainty. From a technical perspective, uncertainty relates to incomplete information regarding the possibility of achieving technical success and the cost associated with it [34]. From a market perspective, uncertainty arises mainly from the competition among rival firms. A software startup normally competes with firms all over the world and enjoys less home-advantage than startups in other industries, such as manufacturing and retailing [35]. Note that, divesting and stabilizing are not appropriate to a firm in a highly-uncertain environment, and therefore do not apply to the product-based software startup that we examine in our research [16].

A Software Startup Operates as an Independent Organization. We view a software startup as an independent organization in the process of becoming an established firm. In a high-tech industry such as the software industry, an established firm often acquires new technology by taking over small innovative firms [36]. In this case the software startup will be incorporated into a larger firm and will therefore cease to exist as such.

3.2 Conceptual Model of Early-Stage Software Start-up Survival

We draw on the theory of resource orchestration [13] to develop a conceptual model of early-stage software start-up survival (see Fig. 1). We now present our independent constructs, the associations between them, and propositions for the associations.

Fig. 1.
figure 1

Conceptual model of software start-up survival

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Constructs. We first examine the constructs of technical IT skills and structuring IT expertise, followed by the associations between the constructs.

Technical IT skills. The realization of an innovative idea relies largely on the technical competence that entrepreneurs bring to a start-up [37]. Therefore, structuring IT expertise is a very important aspect of a software start-up. To structure IT expertise, entrepreneurs need to use technical skills that either exist within a start-up or to which a start-up has access.

Technical IT skills refer to the generic and explicit skills needed for developing IT applications [38, 39]. Generic IT skills include, for example, knowledge of programming, system integration, database management. Explicit IT skills include, for example, the knowledge that is codified in equations, blueprints. Internal technical skills are possessed largely by its founding team in the early stages of development because most of software start-ups consist only of the co-founders. Technical IT skills are not, however, restricted to those within the software start-up itself. The required skills may be provided by IT professionals external to the start-up firm.

Structuring IT expertise. Structuring IT expertise refers to managing the specialized IT knowledge of a start-up [16]. Because software development is knowledge work, its success mainly relies on IT expertise [40]. A team’s expertise derives from the aggregation of individual skills [41]. A start-up operates at a resource disadvantage in its early stages of development [26]. Therefore, entrepreneurs need to acquire necessary knowledge from the external environment. Further, individual knowledge may not be readily transferrable and is, therefore, resistant to elaboration across an organization [42]. Hence, entrepreneurs need to promote internal learning and training to accumulate and structure knowledge within their software start-ups.

Specifically, structuring IT expertise includes two types of actions: acquiring and accumulating expertise. Acquiring refers to obtaining IT expertise from the marketplace [43]. For example, entrepreneurs obtain advice from external IT experts or hire new IT staff to enrich their firm’s IT expertise. Accumulating expertise refers to developing IT expertise internal to a firm. Highly firm-specific resources cannot be bought as commodities from the marketplace; rather, they require internal accumulation [44]. For example, the understanding of the software innovation is the knowledge that needs to be accumulated through learning-by-doing and learning-by-trying [45].

Associations between Constructs. We first examine the association between technical IT skills and structuring IT expertise, followed by the association between structuring IT expertise and software development performance.

Technical IT skills and structuring IT expertise. Technical IT skills aid entrepreneurs in structuring IT expertise in two ways. First, technical IT skills of the founding team in software start-ups facilitate acquiring expertise by enhancing entrepreneurs’ awareness of the value of IT expertise [46]. IT expertise is valuable only when its contribution to a firm exceeds the cost of acquiring it [43]. Appropriate technical IT skills enable entrepreneurs to evaluate more precisely the potential business value provided by IT personnel. Such evaluation is critical for entrepreneurs to prioritize their marketplace acquisitions. That is, entrepreneurs focus efforts on acquiring IT expertise that is most needed in their start-ups.

Second, to accumulate IT expertise, internal technical IT skills must already be in place. Accumulating IT expertise requires training programs [16, 44]. Technical IT skills provide a rich environment in which entrepreneurs design internal training programs. For example, entrepreneurs assign less-experienced IT personnel to work on a software development project along with IT experts that has adequate IT technical skills, which helps nascent employees develop their skills thereby enriching the specialized knowledge of the software start-up. Hence, we propose the following proposition:

P1. Technical IT skills of the founding team are positively associated with structuring IT expertise.

Structuring IT expertise and software development performance. Structuring IT expertise contributes to software development performance because entrepreneurs acquire and accumulate specialized knowledge for prototype development. When IT expertise is present, the likelihood of developing a successful software prototype is high [40]. First, structuring IT expertise is critical for ensuring the effectiveness of a software prototype. If entrepreneurs structure a set of specialized knowledge regarding prototype development, they will help their start-ups develop an accurate understanding of the software functionality and conceptualize a software solution to realize the required functionality [47]. The more effectively entrepreneurs structure IT expertise, the better the possibility of realizing the software innovation.

Second, structuring IT expertise is beneficial for enhancing the efficiency of software development. If entrepreneurs structure their IT expertise appropriately, they are better placed to obtain the knowledge necessary to overcome the technical barriers encountered, thereby accelerating the pace of software development. Further, if entrepreneurs structure IT expertise, a software start-up will be likely to develop a reasonable software development plan based on cost, risk assessment, and schedule [48]. Therefore, we propose the following proposition:

P2. Structuring IT expertise is positively associated with software development performance.

3.3 Boundaries of the Conceptual Model

Three premises underlie our model of early-stage software startup survival. The model will not hold when any of the fundamental premises is violated.

First, the model is only suitable for explaining firm failure due to inefficient managerial actions. For example, failing to structure IT expertise may lead to a software startup’s failure in software development. Expect from inefficient managerial actions, various factors may cause a firm to fail in the marketplace. For example, although the actions entrepreneurs take may be effective for managing a software startup’s resources, a software startup may exit from the industry because of the negative impacts of financial crisis. Such kinds of circumstances are not accounted for in our model.

Second, our theory is only applicable for a software startup that introduces the initial software product and subsequent innovations to the marketplace. Two types of software startups are not accounted for in our model. One refers to software startups that focus on providing outsourcing services for other firms. Such firms repeatedly engage in the process of software development but are not responsible for introducing the software innovation into the marketplace. The other one refers to software startups that outsource completely development tasks to other firms, and therefore they do not engage in product development activities. Technical uncertainty and market uncertainty for such firms are low, so managers may maintain current competitive advantage by stabilizing existing business processes. Managers may also divest resources when they have a full understanding of business environment [16].

Third, a software startup is taken over by another firm is not addressed in our model. Some startups are designed to be sold because their entrepreneurs are more likely to have entrepreneurial preferences [49]. Entrepreneurs, who enjoy starting a new business from scratch, may sell their business after their firms demonstrates viable prototypes and then engage with a new business.

4 Conclusion

We first present the potential contributions of our research, followed by its practical implications. We then present research directions

4.1 Expected Contributions

Our research seeks to contribute theoretically to existing literature in two areas: IS research in general and resource-based theory.

First, our research contributes to IS research by developing a theory of how an early stage software start-up survives. It is important for IS researchers to understand what management in software firms needs to do to facilitate survival. To the best of our knowledge, IS research to date provides few insights into the development of a software start-up.

Second, our research contributes to resource-based theory by explaining how resources and capabilities are deployed to achieve high levels of performance at early stage of a software start-up. Prior research primarily focuses on documenting that a set of resources and capabilities lead to firm performance. Such research is silent on how resources and capabilities are deployed [11, 50]. In our research, we examine the role of managerial actions in using resources and capabilities to achieve firm performance.

4.2 Practical Implications

Our research has major implications for practice. We identify the actions entrepreneurs need to take to manage a software start-up’s resources in the early stages of a software start-up. Resources themselves cannot create value for customers and owners. It is the use of resources that directly leads to business value. Entrepreneurs may facilitate the delivery of innovative software applications and thus compete successfully in the marketplace by effective resource management and resource utilization.

4.3 Research Directions

We present the possibilities of furthering our research. First, researchers can develop measures for the concepts in our conceptual model and collect empirical data to test our conceptual model. Second, researchers can examine the development of software start-ups that are in the late-stage of startup life cycle. Firms in different life-cycle stages require different resources and actions into managing resources [13]. It is meaningful to examine the effects of resources and managerial actions on performance across start-up life cycle stages.