Next Article in Journal
The Synergy Tool: Making Important Quality Gains within One Healthcare Organization
Previous Article in Journal
Fixing the Women or Fixing Universities: Women in HE Leadership
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Administrative Sciences
Volume 7
Issue 3
10.3390/admsci7030031
admsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Communication

Determinants in Competition between Cross-Sector Alliances

by
Stephen Fox
1,*,
Janne Kauttio
1,
Yusuf Mubarak
2 and
Hannu Niemisto
1
1
VTT Technical Research Centre of Finland, Vuorimiehentie FI-02044 VTT, Finland
2
Finland-Somalia Association, Helsinki 00101, Finland
*
Author to whom correspondence should be addressed.
Adm. Sci. 2017, 7(3), 31; https://doi.org/10.3390/admsci7030031
Submission received: 17 July 2017 / Revised: 16 August 2017 / Accepted: 21 August 2017 / Published: 28 August 2017
Browse Figures
Versions Notes

Abstract

:
Private, public, and not-for-profit organizations come together in cross-sector alliance projects and programmes (CSA) to bring about large-scale changes. CSA can often face determined competition from other alliances that oppose large-scale change or propose alterative large-scale changes. Competition can be related to people’s deeply held beliefs arising from their ideologies, cultures, and/or other sources of entrenched preconceptions. In previous CSA research, there has been little consideration of competition between CSA involving people’s deeply held beliefs. Accordingly, in this paper, a conceptual framework for better understanding CSA competition is introduced. This encompasses the influence of people’s beliefs and related underlying determinants. This is necessary because there are many large-scale challenges that involve private, public, and not-for-profit organizations working together in projects and programmes against competition.

1. Introduction

Hitherto, research concerned with cross-sector alliances (CSA) has considered arrangements, resources and cooperation within CSA rather than competition between CSA (Austin 2000; Gomes-Casseres 2003; Koschmann et al. 2012; Love et al. 2016; Marshall et al. 2014; Rufin and Rivera-Santos 2010; Selsky and Parker 2005; Zeng and Chen 2003). However, improving understanding about competition between CSA is also important. In particular, it is important to improve understanding of competition that involves deeply held beliefs. This is because deeply held beliefs can override reasoning and can be the source of intractable conflicts (Barrett 2017; Blackman and Baird 2014; Kahan et al. 2010). For example, capacity building cross-sector alliance projects and programmes (CSA) in fragile states can face brutal opposition from ideology-based CSA, which are fast-moving and highly innovative (Dolnik 2007; Fernandez 2015; Gill et al. 2013; Solomon et al. 2015). Also, CSA in stable countries can be pitted against each other in so-called culture wars. These involve fierce competition between CSA that have opposing beliefs about civil liberty issues (Chapman and Ciment 2014). In addition, new large-scale socio-technical innovations—such as driverless electric vehicles—involve cross-sector competition, which can be rooted in opposing beliefs about the benefits and dangers from technology (Poczter and Jankovic 2014; Smit 2006; Wisniewski 2016). More broadly, some CSA work to win people over to large-scale changes that could be deeply unattractive to people, such as sharing with strangers and the remote monitoring of behaviour (Malhotra and Van Alstyne 2014). Thus, there is competition between CSA that involves deeply held beliefs in settings ranging from fragile states to prosperous nations.
Deeply held beliefs can lead people to make recurring judgements about new situations because they believe them to be the same as old situations. This happens because deeply held beliefs tend to persist even in the face of contradictory information as they provide individuals with belief-based expectations when they receive sensory information (Anderson 2010; Carpenter and Grossberg 2003; Kahan et al. 2013; Voss et al. 2008). Hence, CSA need to have a better understanding of competition that involves people’s deeply held beliefs. Accordingly, a new conceptual framework for CSA competition is introduced in this paper.
The framework is intended to contribute to the evolution of shared mental models. Shared mental models enable different individuals with different backgrounds to be “on the same page” even when they are from different organizations. By contrast, without shared mental models, there can be little common ground among individuals. This can contribute to failures with high human and financial costs. Many cross-sector initiatives seek to address profound issues. Hence, the evolution of shared mental models can be particularly important for CSA (Mathieu et al. 2000; Mohammed et al. 2010).
The research began with exploratory inductive reasoning, moving from observations to conceptualization of the framework. Subsequently, refinement of the framework involved abductive reasoning through iterative cycles of reference to theory and cases (Flach and Hadjiantonis 2013). First, observations and reflections from capacity building projects in a fragile state provided directions for a literature review. In order to investigate to what extent, if any, the observations are found in other settings, an initial literature review was carried out. As there was support in the literature for the observations, a more comprehensive review of theory and cases was carried out. This included news reports about cross-sector cases as well as scientific literature about underlying issues across private, public, and not-for-profit sectors including perception, cognition, and management. Literature reviews informed the development of the framework, which involved frequent iterations guided by consideration of established criteria including comprehensiveness and parsimoniousness (Dubin 1969; Whetten 1989).
The remainder of the paper comprises four sections. Next, literature review findings are reported. Then the conceptual framework is introduced and research propositions are stated. Subsequently, implications are discussed for research and for practice. In conclusion, principal contributions are summarized.

2. Literature Review Findings

2.1. Directions for Literature Review

Directions for the literature review were informed by observations, reflections and discussions related to capacity building projects in a fragile state. The first project began in 2001 and new projects are on-going in 2017. These projects have involved regular interaction with the public sector, not-for-profit sector, private sector, and local people. The importance of people’s predictive evaluations was noted. For example, some young men, who lack positive prospects, predict better personal futures from insurgency alliances than from cross-sector capacity development efforts: especially when insurgency alliances offer them immediate work and rewards such as a monthly salary of 150 US dollars in cash. People’s predictive evaluations are influenced by the originality of organizations’ actions and type of competitors’ responses. For example, many cross-sector capacity building efforts are based on the repetition of typical development approaches. Yet, insurgency movements are inventive in devising competitive tactics for recruiting and rewarding, such as offering joining-up incentives including free mobile phones. Also, organizations’ actions and competitors’ responses can have different reach durations. Previous failures of cross-sector actions to create local employment can create long-lasting scepticism among some local people about future prospects. Past experiences can lead to people’s viewpoint depths being different. For example, negative experiences can lead to increasing reference to—and association with—local ideology-based beliefs, such as preconceptions about outsiders and suspicions about their intentions when undertaking capacity building projects. In particular, the resurgence of local ideology-based beliefs can lead to increasing suspicions that outsiders aim to undermine local ideologies and replace them with foreign ideologies. People’s choices arising from organizations’ actions range from as intended to not as intended. This happens when a few people get jobs with cross-sector alliances, but the majority are alienated by the failures of capacity building to generate lasting large-scale employment. By contrast, insurgency movements can be seen as offering career prospects that are particularly valued because they are not dependent upon outsiders. Overall, it was noted that cross-sector capacity building efforts take place within competitive environments where there can be determined opposing organizations. In order to investigate to what extent, if any, the observations are found in other settings, an initial literature review was carried out. As there was support in the literature for the observations, a more comprehensive review was carried out. Literature review findings are summarized in the following paragraphs.

2.2. People’s Viewpoint Depths

A review of the literature in research fields such as cognition, psychology, marketing, and media studies, indicates that the positive predictive evaluations needed to win people over (Conger 1998) depend much upon people’s viewpoint depths. In particular, deeply held beliefs can be much more resistant to change through updating than temporary whims (Eagly and Chaiken 1995; Kahan et al. 2010; Kim and Pasadeos 2007). For example, cultural learning can lead to individuals having cognitive templates, which provide them with “top-down” expectations as they receive “bottom-up” sensory information (Anderson 2010; Carpenter and Grossberg 2003; Kahan et al. 2013). Hence, spontaneous whims can be related to persistent opinions, which can be related to deep beliefs.

2.3. People’s Predictive Evaluations

Neuroscience research has revealed underlying patterns in people’s predictive evaluations. In particular, people are not likely to be won over if predictive evaluations suggest a negative balance or similar balance, relative to current situations. By contrast, if predictive evaluations suggest a positive balance, then people are more likely to be won over (Clark 2015; Hohwy 2013; Seth 2015). Thus, predictive evaluations can range from won over to not won over. Neuroscience research also indicates that related actions can be perceptually integrated by people to generate a single coherent evaluation (Laurienti et al. 2003).

2.4. Organizations’ Actions

Whether CSA actions are considered in terms of the art of war (Lee et al. 1994) or the art of persuasion (Conger 1998), winning involves determining the appropriate amount of originality in what is offered and how it is offered (Burgelman et al. 1996; Eisenhardt and Tabrizi 1995). For example, alliances in insurgency movements can be highly inventive in their adoption of new technologies, their formulation of new strategies and their shaping of new organizational structures. By contrast, cross-sector alliances facing insurgency movements can be less inventive and more repetitive in their actions (Dolnik 2007). Thus, the actions of organizations can range from repetition to invention. The extent of originality can affect speed of action. (Fine 1998), but it is possible for competitors to make rapid counteractions to even highly inventive actions (Souza et al. 2004).

2.5. Competitors’ Responses

Competitors’ responses can range from no immediate response to retaliatory counteractions—more simply put, from defer to hostile. In a duopoly or oligopoly, for example, a competitor may make no initial response if an action does not seem threatening (Coyne and Horn 2009). Hostile responses are common during intense winner-take-all competition. However, hostile responses can take place within any environment if competitors believe that the actions of others are threatening them, for example, by winning over too many people (Moorthy 1988). In between no immediate response and hostile responses can be equalizing responses when competitors are satisfied with re-establishing their typical share within the status quo (Normann 2000). Competitive responses are as relevant to alliances as to individual organizations. For example, cross-sector alliances within the climate change counter-movement (CCCM) vary their responses to the actions of cross-sector ecological alliances in efforts to maintain the status quo of energy production and consumption (Brulle 2014). However, the potential for making timely competitive responses depends much upon mental models. In particular, managers in organizations that are not used to competition can be slowed by what has been described as cognitive inertia. This can limit their awareness, motivation, and capability amidst competitive dynamics (Chen and Miller 2012). A summary of constructs, together with explanations and references is provided in Table 1.

2.6. Reach Duration

Organizations’ actions and competitors’ responses can have different reach durations. Extreme examples are speeches that reach new generations over decades and even centuries (Calloway-Thomas and Lucaites 2006). The longer the reach duration of an action the greater is the potential for competitors’ responses to exert an influence over people’s predictive evaluations (Ancona et al. 2001; Bridoux et al. 2013).

2.7. People’s Choices

People’s choices arising from organizations’ actions can range from as intended to not as intended. Within complex systems, for example, actions can backfire and have the unintended consequence of pushing people towards competitors (Melzer 2012; Patrick 2013; Sterman 2000). Hence, the causes of people’s choices can be attributed incorrectly to actions, for example, through perceptual biases such as Illusions of Control (Langer 1975) and through unintended consequences such as Balloon Effects (Madsen 2007).

2.8. Competitive Environments

Cross-section alliances seek to bring about large-scale changes in competitive environments including: duopolies, oligopolies, and winner-take-all. For example, governments can take the lead in cross-sector efforts to make their countries seem a more attractive geographical option than another country,i.e., duopoly—more attractive than several other countries, i.e., oligopoly—a more attractive option than every other country, i.e., winner-take-all (Cerna 2014). Also, two cross-sector alliances can be pitted against each other, i.e., duopoly. Alternatively, several alliances can cooperate temporarily against one other alliance in order to bring about change, i.e., oligopoly. Conversely, one cross-sector alliance can be in opposition to many other groups in an effort to maintain its hegemony, i.e., winner-take-all (Chapman and Ciment 2014; Lindaman and Haider-Markel 2002).

3. Framework

3.1. Overview of Framework

The conceptual framework for a better understanding of CSA competition is shown in Figure 1. This comprises the constructs summarized in Table 1 and described in Section 2 above. In particular, the conceptual framework comprises organizations’ actions (from repetition to invention); actions’ reach duration (from zero to indefinite); people’s viewpoint depths (from whims to beliefs); competitors’ responses to actions (from defer to hostile); people’s predictive evaluations (from won over to not won over); people’s choices (from as intended to not intended); and competitive environment (duopolies, oligopolies, and winner-take-all).

3.2. Propositions

Six propositions are explained in the following paragraphs. Propositions are summarized diagrammatically in Figure 2 and supporting examples are summarized in Table 2 together with references.
In addition to initial observations and literature review findings (Eagly and Chaiken 1995; Kahan et al. 2010; Kahan et al. 2013; Kim and Pasadeos 2007), cross-sector cases illustrate how people’s viewpoint depths affect their predictive evaluations. For example, cross-sector Brexit Leave campaigners sharpened negative opinions about pan-EU harmonization, and successfully linked those negative opinions to beliefs about British independence (Inman 2016; Mason and Asthana 2016; Weaver 2016). In the USA, opinions about the meaning of the Constitution’s Second Amendment can bind whims about where to buy personal firearms to beliefs about individual liberty. Hence, the USA Gun Rights alliance’s cross-sector efforts have focused public and political argument to support opinions that the Second Amendment gives an unfettered individual right to firearms ownership (Johnson 2009; Waldman 2014). In China, anti-Japanese alliances link purchasing whims to beliefs about Japanese aggression within Chinese heritage (Gries 2005). Accordingly, the first proposition is stated as:
Proposition 1.
CSA will increase the number of people won over through actions that link different viewpoint depths (whims, opinions, beliefs) about the same issue.
Inter-relationships between whims, opinions and beliefs can be local. For example, to increase congruence with local viewpoint depths, publicity for polio vaccination activities was reduced in Afghanistan, Nigeria, and Pakistan, this being necessary to reduce counteractions against polio vaccination activities by anti-West groups in these countries (Abimbola et al. 2013; Obadare 2005). The failure to recognize local viewpoint depths is an issue in cross-sector capacity building actions. This can lead to situations where largely unemployed local populations do not care about what capacity building projects bring to their communities. For example, local populations may even disassemble completed projects so they can take possession of source materials (Dichter 2003). Conversely, failure to recognize the absence of deeply held beliefs can make hostile cross-sector actions ineffective. For example, when France tried to thwart the forming of an international military coalition by the USA, there were cross-sector calls for boycotts of French products throughout all forms of USA media. Yet, there was no overall boycott effect because there are not deep anti-French beliefs across the USA (Ashenfelter et al. 2007). The importance of understanding local inter-relationships between whims, opinions and beliefs can be stated as the following proposition:
Proposition 2.
CSA will increase the number of people won over through actions that are congruent with local viewpoint depths.
Literature review findings indicate that inventive actions—as well as repetitive actions—can be carried out quickly (Souza et al. 2004). Speed of action can be especially important to winning when competitors are drawing from the same converging socio-technical advances (Bores et al. 2003; Lei 2000). Hence, improvisation is increasingly relevant to cross-sector efforts to win people over (Crossan et al. 2005; Nuñez and Lynn 2012). Improvisation involves composition and implementation converging in time (Moorman and Miner 1998). Rather than being well resourced, composition can involve making do with the materials at hand (Weick 2001). Rather than action being taken slowly with expectation of it being conclusive, action can be taken quickly in the hope of moving forward a little and learning something along the way, such as competitors’ current strengths and weaknesses (Weick 1984). Hence, the third proposition is:
Proposition 3.
CSA will increase the number of people won over through actions that outpace the speed of the competition.
For example, an incisive slogan, such as Clean Coal, can be introduced quickly and disseminated rapidly as a successful counteraction against years of cross-sector lobbying and protesting to end coal as a source of energy (Tyree and Greenleaf 2009). Similarly, the Brexit Leave slogan, Independence Day, was introduced quickly and spread rapidly to amplify cultural beliefs about national sovereignty and attenuate opinions about economic inter-dependencies (Weaver 2016). Another example is fast-moving alliances of insurgent organizations winning against more bureaucratic cross-sector alliances (Gill et al. 2013). More generally, so called hybrid threats involve the rapid formation of loosely-coupled alliances to act against conventional alliances in fragile states (Schroefl and Kaufman 2014; Scott and Moreland 2014).
New organizational approaches can be needed to prevent bureaucracy from stifling improvisation (Crossan et al. 2005; Eisenhardt 1989; Eisenhardt and Tabrizi 1995; Nuñez and Lynn 2012). For example, while the formulation of government regulations for self-driving vehicles is a slow process, the Self-Driving Coalition for Safer Streets was put together quickly by Ford, Google, Lyft, Uber, and Volvo Cars to work with the public sector and not-for-profits to assuage concerns about the safety of self-driving vehicles (Spector 2016). Another example is the introduction of social media “counter speech,” which provides opposing online narratives to those being put forward by insurgent groups. This involves government speeding up action by working together quickly with private companies and not-for-profits (Fernandez 2015; Kuchler and Dyer 2015). Similarly, rapid actions to improve upon slow bureaucratic responses to Europe’s migrant crisis have been taken by quickly-formed cross-sector alliances such as Start-Up Refugees (Fox 2016). Hence, the fourth proposition is:
Proposition 4.
CSA will increase the number of people won over through actions that are not delayed by cross-sector bureaucracy.
The literature review findings reported above indicate that the causes of people’s choices—whether as intended or not as intended by organizations—can be attributed incorrectly to actions (Madsen 2007; Langer 1975). Thus, managers may assume false positives and false negatives in their interpretations of causation. Here, a false positive involves assuming that an action is the cause of an intended positive outcome in people’s choices when, for example, it is competitors’ responses that have had a determining positive influence. This is different to a true positive when an action has caused an intended positive outcome in people’s choices. A false negative involves assuming that an action has brought about an unintended negative outcome in people’s choices when, for example, it is competitors’ responses that have had a determining negative influence. This is different to a true negative when an action has caused an unintended negative outcome in peoples’ choices (Peck and Devore 2011).
Identification of true causation is particularly important in cross-sector alliances where private, public, and not-for-profit organizations are taking actions simultaneously towards agreed goals, but can have individual perspectives about which sector is responsible for winning and for failing (Rein and Stott 2009). For example, which organizations were responsible for what outcomes was a topic of praise and blame rather than evaluation and learning in the Brexit campaign (Erlanger 2016). Hence, the fifth proposition is stated as follows:
Proposition 5.
CSA will increase the number of people won over through identification of true and false causation of people’s choices.
For example, cross-sector organizations’ actions focused on regulating where firearms can be purchased fail to address underlying beliefs about individual liberty (Duggan et al. 2011). This in turn leads to purchases increasing rather than decreasing as potential gun control regulations are perceived as a threat to individual liberty (Melzer 2012; Patrick 2013). Similarly in Europe, cross-sector Brexit Remain campaigners focused on the economic dependency of Britain on the EU, without recognizing the potential for such argumentation to provoke opposing beliefs about British independence. This led to the rejection of the economic argumentation and increasing support for the Leave campaign (Inman 2016; Mason and Asthana 2016; Weaver 2016). Another example is a cross-sector anti-radicalisation programme actually driving students towards radicalisation (Bowcott and Adams 2016).
A summary of propositions, together with examples and references is provided in Table 2.
Importantly, what may have been a true positive in the past can become a true negative in the future. This can happen when organizations fall into success traps, where initial success reinforces repetition (Whyte et al. 1997), and competence traps, where organizations become capable only of repeating the same ways of working (Luchins and Luchins 1987). Thus, what was first a successful action can become enshrined in organizational memory and drawn upon over and over again (Rolfe 2005). Hence, as seen in sectors such pharmaceuticals, reference to true positives in organizational memory can be counterproductive when inventiveness is needed to address major changes in competitive environments (Martinez and Goldstein 2007). Accordingly, what had been true positives in the previous environment can become negative action options in the new environment (Madsen and Desai 2010; Simsek et al. 2014). So it is that exactly the same content in organizational memory can change over time from being characterised by invention to being characterised by repetition and from being followed by positive outcomes in people’s choices to being followed by negative outcomes in people’s choices. Accordingly, the sixth proposition is stated as follows:
Proposition 6.
CSA will increase the number of people won over through regular re-evaluation of choice causation.
For example, re-evaluation of publicity for polio vaccination programmes in Nigeria, Pakistan, and Afghanistan identified that it was counterproductive and concluded that there should be less publicity (Abimbola et al. 2013). Another example is that of the re-evaluation of major deworming programmes revealing that the programmes can have a less positive effect on school attendance than had previously been thought (Aiken et al. 2015). More broadly, the Effective Altruism movement undertakes frequent evidence-based evaluations of what is gained from donations and other investments in cross-sector efforts to improve health and prosperity (MacAskill 2015).

4. Discussion

4.1. Implications for Research

Hitherto, research has considered arrangements, resources and cooperation within CSA (Austin 2000; Love et al. 2016; Zeng and Chen 2003). Here, by contrast, a framework is introduced for CSA competition. While understanding CSA cooperation is important, success depends also upon a better understanding of CSA competition and in particular CSA competition that involves deeply held beliefs. For example, capacity building CSA in fragile states can face brutal opposition based on ideologies, and CSA in stable countries can be pitted against each other in so-called culture wars (Chapman and Ciment 2014; Fernandez 2015; Kuchler and Dyer 2015; Lindaman and Haider-Markel 2002). At the same time, CSA promoting new socio-technical paradigms such as driverless electric vehicles and other applications of artificial intelligence (AI) can face determined opposition (Malhotra and Van Alstyne 2014; Poczter and Jankovic 2014).
As summarized in Figure 1, the contribution of this paper is to introduce a framework for competition between CSA that can transcend sector-specific mental models. This is appropriate because human perceptual constructs can integrate multiple dimensions, such as those from private, public, and not-for-profit sectors to generate coherent behavioural preferences (Anderson 2010; Carpenter and Grossberg 2003). Thus, human predictive evaluations do not have to separate different sectors (Clark 2015; Hohwy 2013; Laurienti et al. 2003; Seth 2015). Rather, affecting people’s predictive evaluations always involves affecting people’s viewpoint depths of varying profoundness, ranging from whims to beliefs (Eagly and Chaiken 1995; Kahan et al. 2013).
Moreover, interpretations of people’s choices are not specific to actions that are intended to be primarily private, public or not-for-profit. Rather, the interpretation of people’s choices involves the phenomena of perception and cognition that are common across those actions intended to be primarily private, public or not-for-profit (Luchins and Luchins 1987; Staw 1976; Sydow et al. 2009). Accordingly, it is appropriate that a framework addressing competition between CSA incorporates common determinants rather than advances separate perspectives such as those of switching costs (Burnham et al. 2003), people flows (Jennissen 2007), and cultural forces (Swanson and Creed 2014).
A direction for future research is to investigate the extent to which one framework can be meaningful to different communities of practice that come together in cross-sector alliance projects (Bowker and Star 1999) and to what extent individuals’ existing mental models can limit their perceptions of the proposed framework (Kimble et al. 2010). Key to the proposed framework are terms such as ‘whim’ and ‘belief’. Whether these terms are considered to be separate states or continuum phases, the differences between them can be hard to define. A prospective (ex-ante) approach is to consider the amount of cultural learning people have been exposed to about a particular viewpoint. A retrospective (ex-post) approach is to consider the extent to which people have sought to defend a viewpoint. Yet, neither of these approaches may be conclusive. For example, people can convert away from their lifetimes’ beliefs, while fatal arguments among friends can arise from differences of opinion about trivial issues (Davis 2016).
More broadly, a fundamental challenge in defining people’s viewpoint depths is that they are latent realities. That is, they exist and can provide explanatory unity for phenomena but they are neither directly observable nor easily described by a single measure (Kline 2011). Hence, it is important for future research to consider different perceptions of key terms among individuals from different sectors, and how different perceptions can be resolved (Francis and Gallard 2005).

4.2. Implications for Practice

From a practical perspective, the framework is relevant to CSA competition in many different settings. Often, actions taken by CSA will be mediated by competitors’ responses. In some cases, actions and counteractions can involve life and death struggles. In such struggles, barriers between the thinking of different individuals can have grave consequences (Brummans et al. 2008; Greve 2005; Kabra et al. 2015). Hence, a common framework is important for practitioners because it can provide the basis for shared mental models among individuals from different organizations. By contrast, without shared mental models, common ground among individuals may not be established. This can contribute to failures with high human and financial costs (Mohammed et al. 2010).
Several implications arise from the proposed framework. First, rather than being concerned with cooperation inside cross-sector alliances, the framework addresses determinants involved in CSA actions to win people over against competition. Parties within CSA often have bases for cooperation through shared objectives. However, it is possible that parties in cross-sector efforts to win people over can spend too much time agreeing with each other and not enough time competing successfully against those who oppose them (Fernandez 2015; Melzer 2012). Moreover, internal agreement is not necessary for CSA to be successful in competition. For example, the Brexit Leave alliance was successful despite being fraught with internal disagreements such as the formation of the Grassroots Out organization following infighting between two other organizations (Vote Leave and LeaveEU) (Dean 2016).
Furthermore, in order to compete successfully, CSA need to better understand the profoundness of people’s viewpoint depths and inter-relationships between viewpoints. For example, a consumption whim about what to purchase and where can be related to a considered opinion about the best way to address a serious issue, which can be related to deeply held cultural beliefs. Thus, seeking only to address where something can be bought does not address the root causes of purchases and so can lead to purchases increasing rather than decreasing (Patrick 2013).
Also, seeking to change beliefs can require considerable inventiveness in action: not just in one action but in many inventive actions that win people over and address counteractions as they emerge. Thus, parties in CSA should benefit from being less concerned about how well they get on with each other and more concerned about their capacity for inventive actions. In particular, parties in CSA can foster inventive excellence through critical argument (De Dreu 2006). This is most important when lack of originality can bring terminal losses in a fiercely contested winner-take-all environment where competitors seek to gain control through shaping beliefs about what is possible. At the same time, CSA should seek to foster improvisational agility that enables them to pre-empt and respond quickly, as well as inventively, to competitors’ actions (Fryer and Loury 2005).
Moreover, parties in CSA need to analyse carefully what works and what does not work in competition. This is necessary to avoid false positives and false negatives in the attribution of action outcomes in people’s choices, and so avoid subsequent inept repetitions. Hence, it is important for CSA to avoid attribution bias where successes and failures are attributed to one figurehead or one particular action. Instead, patterns across actions—and responses to them—should be analysed in order to determine how evolving successes emerge from action (Garud et al. 2008; Moeller 2014).
The proposed framework can contribute to enabling such analyses. In particular, the proposed framework can provide a starting point for the formulation of computational simulation models (Davis et al. 2007). A potential direction for their formulation is to draw upon established mathematical models developed originally for describing behaviour related to influencing customers, to inter-organizational combat, and to environmental perturbances (Prasad and Sethi 2003).

5. Conclusions

Previous work concerning cross-sector alliances has considered arrangements, resources, and cooperation within CSA. By contrast, the overall contribution of this paper is to explain determinants in competition between CSA. This is important because, while understanding cooperation within CSA is important, success depends upon a better understanding of how to deal with competition between CSA. The framework comprises the following principal factors: predictive evaluations, organizations’ actions, competitors’ responses, reach duration, people’s viewpoint depths, people’s choices, and competitive environment. The framework has been used to explain the need for cross-sector alliances to better map viewpoint depths, outpace cross-sector competition, and verify choice causation. The framework is founded upon research into perception and cognition that underlie behaviour in any sector. In addition, the framework encompasses theories of competitive environments, improvisation, and organizational memory. The introduction of a common framework is timely as there are many major challenges that involve private, public and not-for-profit organizations working together in CSA against competition. It is not the purpose of this paper to seek to assert that the proposed conceptual framework is complete and fixed. Rather, it is open to improvement through critical appraisal and through further research as cross-sector competition evolves.

Acknowledgments

This work is partially funded by EU grant number 609143.

Author Contributions

The lead author took the lead in all aspects of the work. Co-authors took a secondary role in all aspects of the work.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Abimbola, Seye, Asmat Ullah Malik, and Ghulam Farooq Mansoor. 2013. The Final Push for Polio Eradication: Addressing the Challenge of Violence in Afghanistan, Pakistan, and Nigeria. PLoS Medicine 10: e1001529. [Google Scholar] [CrossRef] [PubMed]
  2. Aiken, Alexander M., Calum Davey, James R. Hargreaves, and Richard J. Hayes. 2015. Re-analysis of health and educational impacts of a school-based deworming programme in western Kenya: A pure replication. International Journal of Epidemiology 44: 1572–80. [Google Scholar] [CrossRef] [PubMed]
  3. Ancona, Deborah G., Paul S. Goodman, Barbara S. Lawrence, and Michael L. Tushman. 2001. Time: A new research lens. Academy of Management Review 26: 645–63. [Google Scholar]
  4. Anderson, Michael L. 2010. Neural reuse: A fundamental organizational principle of the brain. Behavioral and Brain Sciences 33: 245–313. [Google Scholar] [CrossRef] [PubMed]
  5. Ashenfelter, Orley C., Stephen Ciccarella, and Howard J. Shatz. 2007. French Wine and the U.S. Boycott of 2003: Does Politics Really Affect Commerce? Journal of Wine Economics 2: 55–74. [Google Scholar] [CrossRef]
  6. Austin, James E. 2000. Strategic collaboration between nonprofits and businesses. Nonprofit and Voluntary Sector Quarterly 29: 69–97. [Google Scholar] [CrossRef]
  7. Barrett, Lisa F. 2017. The theory of constructed emotion: An active inference account of interoception and categorization. Social Cognitive and Affective Neuroscience 12: 1–23. [Google Scholar] [CrossRef] [PubMed]
  8. Blackman, Josh, and Shelby Baird. 2014. The shooting cycle. Connecticut Law Review 46: 1513–79. [Google Scholar]
  9. Bores, Cristina, Carme Saurina, and Ricard Torres. 2003. Technological convergence: A strategic persective. Technovation 23: 1–13. [Google Scholar] [CrossRef]
  10. Bowcott, Owen, and Richard Adams. 2016. Human rights group condemns Prevent anti-radicalisation strategy. The Guardian, July 13. [Google Scholar]
  11. Bowker, Geoffrey C., and Susan L. Star. 1999. Sorting Things out: Classification and Its Consequences. Cambridge: MIT Press. [Google Scholar]
  12. Bridoux, Flore, Ken G. Smith, and Curtis M. Grimm. 2013. The management of resources: Temporal effects of different types of actions on performance. Journal of Management 39: 928–57. [Google Scholar] [CrossRef]
  13. Brulle, Robert J. 2014. Institutionalizing delay: Foundation funding and the creation of U.S. climate change counter-movement organizations. Climatic Change 122: 681–94. [Google Scholar] [CrossRef]
  14. Brummans, Boris H. J. M., Linda L. Putnam, Barbara Gray, Ralph Hanke, Roy J. Lewicki, and Carolyn Wiethoff. 2008. Making sense of intractable multiparty conflict: A study of framing in four environmental disputes. Communication Monographs 75: 25–51. [Google Scholar] [CrossRef]
  15. Burgelman, Robert A., Clayton M. Christensen, and Steven C. 1996. Strategic Management of Technology and Innovation, 2nd ed. Chicago: Irwin. [Google Scholar]
  16. Burnham, Thomas A., Judy K. Frels, and Vijay Mahajan. 2003. Consumer switching costs: A typology, antecedents, and consequences. Journal of the Academy of Marketing Science 31: 109–26. [Google Scholar] [CrossRef]
  17. Calloway-Thomas, Carolyn, and John L. Lucaites. 2006. Martin Luther King Jr. and the Sermonic Power of Public Discourse. Tuscaloosa: The University of Alabama Press. [Google Scholar]
  18. Carpenter, Gail A., and Stephen Grossberg. 2003. Adaptive resonance theory. In The Handbook of Brain Theory and Neural Networks, 2nd ed. Edited by M. A. Arbib. Cambridge: MIT Press, pp. 87–90. [Google Scholar]
  19. Cerna, Lucie. 2014. Attracting High-Skilled Immigrants: Policies in Comparative Perspective. International Migration 52: 69–84. [Google Scholar] [CrossRef]
  20. Chapman, Roger, and James Ciment. 2014. Culture Wars: An Encyclopedia of Issues, Viewpoints and Voices, 2nd ed. Abingdon: Routledge. [Google Scholar]
  21. Chen, Ming-Jer, and Danny Miller. 2012. Competitive Dynamics: Themes, Trends, and a Prospective Research Platform. Academy of Management Annals 6: 1–89. [Google Scholar] [CrossRef]
  22. Clark, Andy. 2015. Embodied prediction. In Open MIND. Edited by Thomas Metzinger and Jennifer. M. Windt. Frankfurt: MIND Group, pp. 1–21. [Google Scholar]
  23. Conger, Jay A. 1998. Winning ‘Em over: A New Model for Managing in the Age of Persuasion. New York: Simon and Schuster. [Google Scholar]
  24. Coyne, Kevin P., and John Horn. 2009. Predicting your competitor’s reaction. Harvard Business Review 87: 90–97. [Google Scholar]
  25. Crossan, Mary, Miguel Pina E. Cunha, Dusya Vera, and João Cunha. 2005. Time and Organizational Improvisation. Academy of Management Review 30: 129–45. [Google Scholar] [CrossRef]
  26. Davis, Callum. 2016. Man kills his friend in argument. The Telegraph, March 7. [Google Scholar]
  27. Davis, Jason P., Kathleen M. Eisenhardt, and Christopher B. Bingham. 2007. Developing theory through simulation methods. Academy of Management Review 32: 480–99. [Google Scholar] [CrossRef]
  28. Dean, Will. 2016. Faction stations: Which Brexit campaign is which? The Guardian, January 31. [Google Scholar]
  29. De Dreu, Carsten K. W. 2006. When Too Little or Too Much Hurts: Evidence for a Curvilinear Relationship Between Task Conflict and Innovation in Teams. Journal of Management 32: 83–107. [Google Scholar] [CrossRef]
  30. Dichter, Thomas W. 2003. Despite Good Intentions: Why Development Assistance to the Third World Has Failed. Amherst: University of Massachusetts Press. [Google Scholar]
  31. Dolnik, Adam. 2007. Understanding Terrorist Innovation Trends. London: Routledge. [Google Scholar]
  32. Dubin, Robert. 1969. Theory Building. New York: Free Press. [Google Scholar]
  33. Duggan, Mark, Randi Hjalmarsson, and Brian A. Jacob. 2011. The Short-Term and Localized Effect of Gun Shows: Evidence from California and Texas. Review of Economics and Statistics 93: 786–99. [Google Scholar] [CrossRef]
  34. Eagly, Alice H., and Shelly Chaiken. 1995. Attitude strength, attitude structure, and resistance to change. In Attitude Strength: Antecedents and Consequences. Edited by Richard E. Petty and Jon A. Krosnick. London: Psychology Press, Taylor & Francis Group, pp. 413–32. [Google Scholar]
  35. Eisenhardt, Kathleen M. 1989. Making fast strategic decisions in high-velocity environments. Academy of Management Journal 32: 543–76. [Google Scholar] [CrossRef]
  36. Eisenhardt, Kathleen M., and Behnam N. Tabrizi. 1995. Accelerating adaptative processes: Product innovation in the global computer industry. Administrative Science Quarterly 40: 84–110. [Google Scholar] [CrossRef]
  37. Erlanger, Steven. 2016. Fractures From ‘Brexit’ Vote Spread Into Opposition Labour Party. The New York Times, June 26. [Google Scholar]
  38. Fernandez, Alberto M. 2015. Here to Stay and Growing: Combating ISIS Propaganda Networks. The Brookings Project on U.S. Relations with the Islamic World Center for Middle East Policy at Brookings. Available online: https://www.brookings.edu/wp-content/uploads/2016/07/IS-Propaganda_Web_English_v2.pdf (accessed on 20 February 2017).
  39. Fershtman, Chaim, and Kenneth L. Judd. 1987. Equilibrium Incentives in Oligopoly. The American Economic Review 77: 927–40. [Google Scholar]
  40. Fine, Charles H. 1998. Clockspeed: Winning Industrial Control in the Age of Temporary Advantage. New York: Perseus Books. [Google Scholar]
  41. Flach, Peter A., and Antonis M. Hadjiantonis. 2013. Abduction and Induction: Essays on Their Relation and Integration. Dordrecht: Springer Science & Business Media, vol. 18. [Google Scholar]
  42. Fox, Stephen. 2016. Addressing the causes of mass migrations: Leapfrog solutions for mutual prosperity growth between regions of emigration and regions of immigration. Technology in Society 46: 35–39. [Google Scholar] [CrossRef]
  43. Francis, Wendy S., and Sabrina L. K. Gallard. 2005. Concept mediation in trilingual translation. Psychonomic Bulletin and Review 12: 1082–88. [Google Scholar] [CrossRef] [PubMed]
  44. Fryer, Roland G., and Glenn C. Loury. 2005. Affirmative action in winner-take-all markets. Journal of Economic Inequality 3: 263–80. [Google Scholar] [CrossRef]
  45. Garud, Raghu, Sanjay Jain, and Phillipp Tuertscher. 2008. Incompleteness by design and designing for incompleteness. Organizational Studies 29: 351–71. [Google Scholar] [CrossRef]
  46. Gill, Paul, John Horgan, Samuel T. Hunter, and Lily D. Cushenbery. 2013. Malevolent creativity in terrorist organizations. The Journal of Creative Behaviour 47: 125–51. [Google Scholar] [CrossRef]
  47. Gomes-Casseres, Benjamin. 2003. Competitive advantage in alliance constellations. Strategic Organization 1: 327–35. [Google Scholar] [CrossRef]
  48. Greve, Henrich. R. 2005. Interorganizational Learning before 9/11. International Public Management Journal 8: 383–90. [Google Scholar] [CrossRef]
  49. Gries, Peter H. 2005. Nationalism, Indignation, and China’s Japan Policy. SAIS Review of International Affairs 25: 105–14. [Google Scholar] [CrossRef]
  50. Hohwy, Jakob. 2013. The Predictive Mind. Oxford: Oxford University Press. [Google Scholar]
  51. Inman, Phillip. 2016. Mervyn King: Treasury’s exaggerated Brexit claims backfired. The Guardian, June 27. [Google Scholar]
  52. Jennissen, Roel. 2007. Causality Chains in the International Migration Systems Approach. Population Research and Policy Review 26: 411–36. [Google Scholar] [CrossRef]
  53. Johnson, Nicholas J. 2009. A Second Amendment Moment: The Constitutional Politics of Gun Control. Brooklyn Law Review 71: 715. [Google Scholar]
  54. Kabra, Gaurav, Anbanandam Ramesh, and Kaur Arshinder. 2015. Identification and prioritization of coordination barriers in humanitarian supply chain management. International Journal of Disaster Risk Reduction 13: 128–38. [Google Scholar] [CrossRef]
  55. Kahan, Dan, Hank Jenkins-Smith, and Donald Braman. 2010. Cultural Cognition of Scientific Consensus. Journal of Risk Research 14: 147–74. [Google Scholar] [CrossRef]
  56. Kahan, Dan M., Ellen Peters, Erica C. Dawson, and Paul Slovic. 2013. Motivated Numeracy and Enlightened Self-Government. Behavioural Public Policy 1: 54–86. [Google Scholar] [CrossRef]
  57. Kim, Kyun S., and Yorgo Pasadeos. 2007. Study of partisan news readers reveals hostile media perceptions of balanced stories. Newspaper Research Journal 28: 99–106. [Google Scholar] [CrossRef]
  58. Kimble, Chris, Corinne Grenier, and Karine Goglio-Primard. 2010. Innovation and Knowledge Sharing Across Professional Boundaries: Political Interplay between Boundary Objects and Brokers. International Journal of Information Management 30: 437–44. [Google Scholar] [CrossRef] [Green Version]
  59. Kline, Rex B. 2011. Principles and Practice of Structural Equation Modeling. New York: Guilford. [Google Scholar]
  60. Koschmann, Matthew A., Timothy R. Kuhn, and Michael D. Pfarrer. 2012. A communicative framework of value in cross-sector partnerships. Academy of Management Review 37: 332–54. [Google Scholar] [CrossRef]
  61. Kuchler, Hannah, and Geoff Dyer. 2015. Abdullah-X takes on Isis in social media fight. The Financial Times, December 13. [Google Scholar]
  62. Langer, Ellen J. 1975. The Illusion of Control. Journal of Personality and Social Psychology 32: 311–28. [Google Scholar] [CrossRef]
  63. Laurienti, Paul J., Mark T. Wallace, Joseph A. Maldjian, Christina M. Susi, Barry E. Stein, and Jonathan H. Burdette. 2003. Cross-modal sensory processing in the anterior cingulate and medial prefrontal cortices. Human Brain Mapping 19: 213–23. [Google Scholar] [CrossRef] [PubMed]
  64. Lee, Khai. S., Pheng L. Chng, and Chow H. Wee. 1994. The art and the science of strategic marketing: Synergizing Sun Tzu’s Art of War with game theory. Journal of Strategic Marketing 2: 49–60. [Google Scholar] [CrossRef]
  65. Lei, David T. 2000. Industry evolution and competence development: The imperatives of technological convergence. International Journal of Technology Management 19: 699–738. [Google Scholar] [CrossRef]
  66. Lindaman, Kara, and Donald P. Haider-Markel. 2002. Issue Evolution, Political Parties, and the Culture Wars. Political Research Quarterly 55: 91–110. [Google Scholar] [CrossRef]
  67. Love, Peter E. D., Pauline Teo, Murray Davidson, Shaun Cumming, and John Morrison. 2016. Building absorptive capacity in an alliance: Process improvement through lessons learned. International Journal of Project Management 34: 1123–37. [Google Scholar] [CrossRef]
  68. Luchins, Abraham S., and Edith H. Luchins. 1987. Einstellung effects. Science 238: 598. [Google Scholar] [CrossRef]
  69. Madsen, Kenneth D. 2007. Local Impacts of the Balloon Effect of Border Law Enforcement. Geopolitics 12: 280–98. [Google Scholar] [CrossRef]
  70. Madsen, Peter M., and Vinit Desai. 2010. Failing to learn? The effects of failure and success on organizational learning in the global orbital launch vehicle industry. Academy of Management Journal 53: 451–76. [Google Scholar] [CrossRef]
  71. Malhotra, Arvind, and Marshall Van Alstyne. 2014. The dark side of the sharing economy … and how to lighten it. Communications of the ACM 57: 24–27. [Google Scholar] [CrossRef]
  72. Marshall, Alasdair, Udechukwu Ojiako, and Max Chipulu. 2014. Micro-political risk factors for strategic alliances: Why Machiavelli’s animal spirits matter. Competition and Change 18: 438–53. [Google Scholar] [CrossRef]
  73. Martinez, Barbara, and Jacob Goldstein. 2007. Big Pharma Faces Grim Prognosis: Industry Fails to Find New Drugs to Replace Wonders Like Lipitor. Wall Street Journal, December 6, AI. [Google Scholar]
  74. Mason, Rowena, and Anushka Asthana. 2016. Brexit would put a bomb under UK economy, says Cameron. The Guardian, June 6. [Google Scholar]
  75. Mathieu, John E., Tonia S. Heffner, Gerald F. Goodwin, Eduardo Salas, and Janis A. Cannon-Bowers. 2000. The influence of shared mental models on team process and performance. Journal of Applied Psychology 85: 273–83. [Google Scholar] [CrossRef] [PubMed]
  76. MacAskill, William. 2015. Doing Good Better—Effective Altruism and a Radical Way to Make a Difference. New York: Avery. [Google Scholar]
  77. McConnell, Campbell R., Stanley L. Brue, and Sean M. Flynn. 2014. Economics: Principles, Problems and Policies, 20th ed. Boston: Irvin/McGraw-Hill. [Google Scholar]
  78. Melzer, Scott. 2012. Gun Crusaders: The NRA’s Culture War. New York: New York University Press. [Google Scholar]
  79. Moeller, Joergen O. 2014. Maskirovka: Russia’s Masterful Use of Deception in Ukraine. The Huffington Post, April 23. [Google Scholar]
  80. Mohammed, Susan, Lori Ferzandi, and Katherine Hamilton. 2010. Metaphor No More: A 15-Year Review of the Team Mental Model Construct. Journal of Management 36: 876–910. [Google Scholar] [CrossRef]
  81. Moorthy, K. Sridhar. 1988. Product and Price Competition in a Duopoly. Marketing Science 7: 141–68. [Google Scholar] [CrossRef]
  82. Moorman, Christine, and Anne S. Miner. 1998. Organizational improvisation and organizational memory. Academy of Management Review 23: 698–723. [Google Scholar]
  83. Normann, Hans-Theo. 2000. Conscious Parallelism in Asymmetric Oligopoly. Metroeconomica 51: 343–66. [Google Scholar] [CrossRef]
  84. Nuñez, Enrique, and Gary S. Lynn. 2012. The impact of adding improvisation to sequential NPD processes on cost: The moderating effects of turbulence. Academy of Marketing Studies Journal 16: 1–18. [Google Scholar]
  85. Obadare, Ebenezer. 2005. A crisis of trust: History, politics, religion and the polio controversy in Northern Nigeria. Patterns of Prejudice 39: 265–84. [Google Scholar] [CrossRef]
  86. Patrick, Brian A. 2013. The National Rifle Association and the Media: The Motivating Force of Negative Coverage. London: Arktos Media Ltd. [Google Scholar]
  87. Peck, Roxy, and Jay L. Devore. 2011. Statistics: The Exploration and Analysis of Data. Boston: Cengage. [Google Scholar]
  88. Poczter, Sharon L., and Luka M. Jankovic. 2014. The Google Car: Driving Toward a Better Future? Journal of Business Case Studies 10: 7–14. [Google Scholar] [CrossRef]
  89. Prasad, Ashutosh, and Suresh P. Sethi. 2003. Competitive advertising under uncertainty: A stochastic differential game approach. Journal of Optimization Theory and Applications 123: 163–85. [Google Scholar] [CrossRef]
  90. Rasmussen, Maria J, and Mohammed M. Hafez. 2010. Terrorist Innovations in Weapons of Mass Effect: Preconditions, Causes and Predictive Indicators. Report No. ASCO 2010-019. Washington: The Defense Threat Reduction Agency. [Google Scholar]
  91. Rein, Melanie, and Leda Stott. 2009. Working together: Critical perspectives on six cross-sector partnerships in southern Africa. Journal of Business Ethics 90: 79–89. [Google Scholar] [CrossRef]
  92. Rolfe, Brett. 2005. Building an Electronic Repertoire of Contention. Social Movement Studies 4: 65–74. [Google Scholar] [CrossRef]
  93. Rufin, Carlos, and Miguel Rivera-Santos. 2010. Between commonwealth and competition: Understanding the governance of public–private partnerships. Journal of Management 36: 1–21. [Google Scholar]
  94. Schroefl, Josef, and Stuart J. Kaufman. 2014. Hybrid Actors, Tactical Variety: Rethinking Asymmetric and Hybrid War. Studies in Conflict and Terrorism 37: 862–80. [Google Scholar] [CrossRef]
  95. Scott, J., and S. Moreland. 2014. The Islamic State is a Hybrid Threat: Why Does That Matter? Small Wars Journal, December 2. [Google Scholar]
  96. Selsky, John W., and Barbara Parker. 2005. Cross-Sector Partnerships to Address Social Issues: Challenges to Theory and Practice. Journal of Management 31: 849–73. [Google Scholar] [CrossRef]
  97. Seth, Anil K. 2015. The Cybernetic Bayesian Brain—From Interoceptive Inference to Sensorimotor Contingencies. In Open MIND: 35(T). Edited by Thomas Metzinger and Jennifer M. Windt. Frankfurt: MIND Group. [Google Scholar]
  98. Simsek, Zeki, Brian C. Fox, and Ciaran Heavey. 2014. "What’s Past Is Prologue": A Framework, Review, and Future Directions for Organizational Research on Imprinting. Journal of Management 41: 288–317. [Google Scholar] [CrossRef]
  99. Smit, Martijntje. 2006. Taming monsters: The cultural domestication of new technologies. Technology in Society 28: 489–504. [Google Scholar] [CrossRef]
  100. Solomon, Erika, Guy Chazan, and Sam Jones. 2015. Isis Inc: How oil fuels the jihadi terrorists. The Financial Times, October 14. [Google Scholar]
  101. Souza, Gilvan C., Barry L. Bayus, and Harvey M. Wagner. 2004. New-product strategy and industry clockspeed. Management Science 50: 537–49. [Google Scholar] [CrossRef]
  102. Spector, Mike. 2016. Obama Administration Rolls out Recommendations for Driverless Cars. The Wall Street Journal, September 19. [Google Scholar]
  103. Staw, B. M. 1976. Knee-deep-in-the-big-muddy: A study of escalating commitment to a chosen course of action. Organisational Behaviour and Human Performance 16: 27–44. [Google Scholar] [CrossRef]
  104. Sterman, John D. 2000. Business Dynamics: Systems Thinking and Modeling for a Complex World. New York: McGraw-Hill. [Google Scholar]
  105. Swanson, Donald J., and Andrew S. Creed. 2014. Sharpening the Focus of Force Field Analysis. Journal of Change Management 14: 28–47. [Google Scholar] [CrossRef]
  106. Sydow, Jörg, Georg Schreyogg, and Jochen Koch. 2009. Organizational path dependence: Opening the black box. Academy of Management Review 34: 689–709. [Google Scholar] [CrossRef]
  107. Tyree, Stephanie, and Maron Greenleaf. 2009. The Environmental Injustice of "Clean Coal": Expanding the national conversation on carbon capture and storage technology to include analysis of potential environmental justice impacts. Environmental Justice 2: 167–71. [Google Scholar] [CrossRef]
  108. Voss, Andreas, Klaus Rothermund, and Jochen Brandtstädter. 2008. Interpreting ambiguous stimuli: Separating perceptual and judgmental biases. Journal of Experimental Social Psychology 44: 1048–56. [Google Scholar] [CrossRef]
  109. Waldman, Michael. 2014. How the NRA rewrote the Second Amendment. Politico, May 19. [Google Scholar]
  110. Weaver, Matthew. 2016. Boris Johnson’s Independence Day claim nonsense, says David Cameron. The Guardian, June 22. [Google Scholar]
  111. Weick, Karl E. 2001. Making Sense of the Organization. Malden: Blackwell. [Google Scholar]
  112. Weick, Karl. E. 1984. Small wins. American Psychologist 39: 40–49. [Google Scholar] [CrossRef]
  113. Whetten, David. 1989. What constitutes a theoretical contribution? Academy of Management Review 14: 490–95. [Google Scholar] [CrossRef]
  114. Whyte, Glen, Alan M. Saks, and Sterling Hook. 1997. When success breeds failure: The role of self-efficacy in escalating commitment to a losing course of action. Journal of Organizational Behavior 18: 415–32. [Google Scholar] [CrossRef]
  115. Wisniewski, Mary. 2016. Driverless cars could improve safety, but impact on jobs, transit questioned. Chicago Tribune, July 4. [Google Scholar]
  116. Zeng, Ming, and Xiao-Ping Chen. 2003. Achieving cooperation in multiparty alliances: A social dilemma approach to partnership management. Academy of Management Review 28: 587–605. [Google Scholar]
Admsci 07 00031 g001 550
Figure 1. Framework.
Figure 1. Framework.
Admsci 07 00031 g001
Admsci 07 00031 g002 550
Figure 2. Propositions.
Figure 2. Propositions.
Admsci 07 00031 g002
Table
Table 1. Summary of constructs.
Table 1. Summary of constructs.
ConstructsExplanationReferences
People’s predictive evaluations (won over—not won over)People are more likely to be won over if predictive evaluations suggest a positive balance relative to their current situations(Clark 2015; Hohwy 2013; Seth 2015)
Organizations’ actions (repetition—invention)Winning involves determining the appropriate amount of originality in what is offered and how it is offered(Dolnik 2007; Rasmussen and Hafez 2010)
Reach duration (zero—indefinite)The longer the reach duration, the more potential for competitors’ responses to exert influence over people’s predictive evaluations(Ancona et al. 2001; Bridoux et al. 2013)
People’s viewpoint depths (whim—belief)Winning depends much upon the profoundness of people’s points of view, with deeply held beliefs being most resistant to change(Eagly and Chaiken 1995; Kahan et al. 2010)
Competitors’ responses (defer—hostile)Across sectors, competitors’ responses can range from none immediately to retaliatory counteractions to protect positions(Coyne and Horn 2009; Fershtman and Judd 1987; Moorthy 1988 )
People’s choices (as intended—not as intended)People’s choices can be as intended to arise from the organizations’ actions, but unintended consequences can also arise(Melzer 2012; Patrick 2013; Sterman 2000)
Competitive environments (duopoly—winner-takes all)Competitive environments cross different types of sectors as governments and not-for-profits also compete to win people over(Cerna 2014; Lindaman and Haider-Markel 2002; McConnell et al. 2014)
Table
Table 2. Summary of propositions.
Table 2. Summary of propositions.
PropositionsExamples
1CSA will increase the number of people won over through actions that link different viewpoint depths
  • Gun Rights alliance links gun purchase whims to beliefs about individual liberty (Waldman 2014).
  • Anti-Japanese alliance in China links purchase whims to anti-Japanese beliefs (Gries 2005).
  • Brexit Leave alliance linked bad opinions about EU to beliefs about UK independence (Weaver 2016).
2CSA will increase the number of people won over through actions that are congruent with local viewpoint depths
  • Local congruence increased by reducing polio vaccination publicity (Obadare 2005).
  • Failure to recognize local viewpoint depths is a common issue in capacity building (Dichter 2003).
  • Calls for USA boycott against France failed due to lack of anti-French beliefs (Ashenfelter et al. 2007).
3CSA will increase the number of people won over through actions that outpace the speed of competition
4CSA will increase the number of people won over through actions that are not delayed by cross-sector bureaucracy
  • Cross-sector alliances combine to rapidly introduce online “counter speech” (Kuchler and Dyer 2015).
  • Self-Driving Coalition for Safer Streets formed quickly to ease safety concerns (Spector 2016). Start-Up Refugees address slow bureaucratic responses to European migrant crisis (Fox 2016).
5CSA will increase the number of people won over through identification of true and false choice causation
  • Gun Control actions lead to gun sales as regulations are seen as being against liberty (Patrick 2013).
  • Brexit Remain provoked independence beliefs by alleging UK is dependent on EU (Inman 2016).
  • Cross-sector anti-radicalisation programme actually causes radicalisation (Bowcott and Adams 2016).
6CSA will increase the number of people won over through regular re-evaluations of choice causation
  • Re-evaluation of polio vaccination publicity found it was counterproductive (Abimbola et al. 2013).
  • Re-evaluation of major deworming programmes found them to be less effective (Aiken et al. 2015).
  • Effective Altruism re-evaluates cross-sector donations to improve prosperity (MacAskill 2015).

Share and Cite

MDPI and ACS Style

Fox, S.; Kauttio, J.; Mubarak, Y.; Niemisto, H. Determinants in Competition between Cross-Sector Alliances. Adm. Sci. 2017, 7, 31. https://doi.org/10.3390/admsci7030031

AMA Style

Fox S, Kauttio J, Mubarak Y, Niemisto H. Determinants in Competition between Cross-Sector Alliances. Administrative Sciences. 2017; 7(3):31. https://doi.org/10.3390/admsci7030031

Chicago/Turabian Style

Fox, Stephen, Janne Kauttio, Yusuf Mubarak, and Hannu Niemisto. 2017. "Determinants in Competition between Cross-Sector Alliances" Administrative Sciences 7, no. 3: 31. https://doi.org/10.3390/admsci7030031

APA Style

Fox, S., Kauttio, J., Mubarak, Y., & Niemisto, H. (2017). Determinants in Competition between Cross-Sector Alliances. Administrative Sciences, 7(3), 31. https://doi.org/10.3390/admsci7030031

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop