A configurational model of reward-based crowdfunding project characteristics and operational approaches to delivery performance

Highlights

• The configurational models are paths to reward-based crowdfunding delivery performance.

• Project venture status is necessary to antecedent delivery performance outcome.

• Proactive and post-campaign sourcing, outsourced and in-house production are causal conditions.

• Different recipes exist for on-time and late delivery performance.

Abstract

Reward-based crowdfunding projects promise funders various kinds of rewards for contributing to their funding goals. After successful funding, the funders expect the project owners to deliver the promised rewards within the specified delivery time. Contrary to crowdfunding research based on conventional symmetric thinking, this research investigates the crowdfunded projects using asymmetric analytics to identify different configurational paths to delivery performance. Using data from the Kickstarter crowdfunding platform, Qualitative Comparative Analysis (QCA) was conducted for the antecedent factors, including project venture status, promised lead time, and sourcing as well as production approaches. The findings indicate that the configurational models, with high consistency and coverage, are sufficient antecedent conditions for on-time and late delivery. Further, the results confirm that a single antecedent condition cannot solely produce an outcome but should be incorporated with other conditions to produce an intended outcome. The findings offer insights into the setting of realistic promised lead times that can be combined with other antecedent conditions to achieve on-time delivery. This research supports the complexity theory and extends its application to crowdfunding research by emphasizing that the approaches for on-time reward delivery performance are unique and not mirror opposites of those applied in late reward delivery performance. Further implications are drawn for crowdfunding stakeholders.

Introduction

Crowdfunding is a new Internet-based financial model that supports entrepreneurs who intend to raise funds for their projects from a relatively large number of individuals without standard financial intermediaries [1]. There are various crowdfunding models such as donation-based, lending-based, equity-based, and reward-based. Among these models, the most popular and frequently applied is reward-based crowdfunding [2]. Reward-based crowdfunding (RBCF) is a new form of entrepreneurial finance in which investors do not receive cash returns from the project venture but rather receive non-monetary rewards for their investments [3]. Due to the popularity of this model, exploring its dynamics would be of much interest to stakeholders and academics. Hence, this research focuses on RBCF.

Currently, crowdfunding research focuses on success factors [[4], [5], [6], [7], [8], [9]] and the motivations for sponsors [[10], [11], [12], [13]]. In the project implementation phase, research has focused on the factors that are responsible for delivery delays [2,[14], [15], [16], [17], [18]]. Crowdfunding literature has emphasized the need for projects to have an operational plan for the delivery of promised rewards to reduce the challenges in the implementation phase, and to improve on delivery performance [[17], [18], [19]]. An operational plan is an approach to be applied for sourcing and production of promised rewards. However, the choice of an operational approach to improve delivery performance depends on certain essential project characteristics. Based on the literature on crowdfunding success, this study considers the essential project characteristics (i.e., project venture status, promised lead time) which are deemed to influence delivery performance. The combinatory effect of the operational approaches for sourcing and production, project venture status, and the promised lead time would either have a positive or negative effect on the delivery performance. It can be inferred that there exists a need for multiple operational configurations to be pursued for projects with different venture status in order to achieve the desired delivery performance outcome. Besides, there is a need for configurations that can support crowdfunding projects in setting realistic promised lead times for on-time delivery. This is because different operational approaches, coupled with a project venture status (i.e., a newly created venture or an existing startup venture), require specific time frames to be able to complete the entire process of reward delivery. For instance, an already existing project venture with an established supply network would need a shorter promised lead time than a newly created project venture with no established supply network. Therefore, understanding such configurations would help RBCF projects to reduce the challenges in the implementation phase and achieve on-time delivery. However, in crowdfunding literature, little evidence exists on such configuration research.

As a contribution to this gap, this study applies a fuzzy set-Qualitative Comparative Analysis (set-QCA), a set-membership analytical technique to explore the configurations of project venture status, promised lead time, sourcing approaches (i.e., proactive sourcing, post-campaign sourcing), and production approaches (i.e., in-house production, outsourced production) that lead to on-time or late delivery performance. Furthermore, such configurations seek to serve as the basis for setting appropriate promised lead times for the various categories of ventures that utilize RBCF. The choice of this method is based on the idea that relations are usually better understood through set-theoretic relations rather than correlations [21,22]. This analytical approach, grounded in set and complexity theories as well as Boolean algebra, allows for a detailed analysis of how antecedent conditions contribute to an outcome in question.

The findings indicate that the configurational models, consisting of antecedent conditions with high consistency and coverage, are sufficient to predict on-time and late delivery. The results also indicate the combinatory conditions for which an antecedent has a positive effect on the outcome as well as the combinatory condition for when an antecedent has a negative influence on the outcome in a multiple path set. Therefore, the models confirm that a single antecedent condition cannot solely produce an outcome but should be incorporated with other conditions to produce an outcome. Furthermore, the findings suggest that antecedent conditions for on-time delivery are unique compared to the ones for late delivery. Lastly, the models offer insights into the setting of appropriate or realistic promised lead times that can be combined with other antecedent conditions to achieve on-time delivery.

The sections are organized as follows. Section 2 is a literature review on crowdfunding. Section 3 is on the development of set-theoretical hypotheses. The presentation and explanation of data collection follow in Section 4. The fifth section presents the results, followed by a discussion of the findings and the conclusion in Section 6.