Water scarcity is one of the major challenges facing the world today [1
]. UN-Water defines water scarcity as either physical water shortage or inaccessibility caused by failed water supply systems or inadequate water infrastructures [3
]. The problem with this defnition is it combines water deficit and water scarcity in one defintion, which can be misleading or inaccurate in circumstances where there is no water deficit but only water scarcity. Jaeger et al. [7
] explain that water scarcity should be distinguished from water deficit. Water scarcity is normative and anthropocentric in nature because it varies based on temporal, spatial and social values (direct and indirect ) regarding multiple water uses. We adopt the Kampas and Rozakis [8
] (p. 1258) definition of water scarcity as “the opportunity costs of forgone human options that result from a specific water use decision”. Jaeger et al. [7
] explain that water deficit is purely descriptive. Kampas and Rozakis [8
] (p. 1258) define water deficit as “the case where the water is not enough for a specific biophysical process”.
United Nations (UN) Food and Agriculture Organization (FAO) statistics indicate that approximately one-fifth of the global population is living in a water scarce area and one quarter suffer as a result of economic water scarcity [2
]. Economic water scarcity occurs when there is sufficient water (no water deficit) but no infrastructure or strong governance system to increase access. The Global Water Insititute records that approximately 700 million persons in 43 states face water scarcity [9
]. The United Nations Educational, Scientific and Cultural Organization (UNESCO) affirms that in 2018, 3.6 billion people lived in water scarce regions with a projected increment to 4.8–5.7 billion in 2050 [1
]. The UN Convention to Combat Desertification (UNCCD) climate change scenario predicts large numbers of persons, upto 700 million, being displaced from arid and semi-arid areas by 2030 [3
]. When the surface water is limited, most countries quickly shift strategy and tap into groundwater resources [10
]. Richey et al. [4
] ascertain that by 2015, one-third of the largest ground water resources were distressed.
Anthropogenic interventions and activities to water, soil and air systems are the main contributors to water scarcity, within a given river basin [5
]. Thus there is need for cooperation within a shared river basin to sustainably manage and control anthropogenic interventions and activities [11
]. In a shared river basin, there will always be in-group and out-group tensions as diverse teams are negotiating to minimise human actions and interventions that threaten current and future water security [6
]. Therefore, the negotiation team needs to create a willingness amongst the different riparian states to cooperate and sustain the cooperation [13
Research indicates that the inability of transboundary water negotiation teams to arrive at a win-win solution [24
] is a major barrier to cooperation [13
] for a given river basin [11
]. According to research, one approach to counter win-lose solutions is introducing a shared superordinate identity (SSI) to surpass in and out-group differences [26
]. SSI creates a perception that the riparian governments belong to one group even though they represent different states or local governments [27
]. It reduces competition, increases cooperation and helps to avoid one-sided outcomes [30
]. It also spurs innovation leading to knowledge creation, knowledge transfer and improved negotiation outcomes [33
] According to Gaertner et al. [30
], SSI can bridge cultural divides and reduce inter-group conflicts [32
]. It also creates an enabling environment for developing both bonding (in-group) and bridging (out-group) social capital [34
]. Putnam [36
] defines social capital as “social networks and the associated norms of reciprocity and trustworthiness” [36
] (p. 137). Bonding social capital in a river basin binds the people within a given riparian state. Bridging social capital on the other hand, builds bridges between different riparains states sharing the drainage basin [36
] (p. 143). Climate change has been one of the effective tools to create SSI [17
]. Through concerted climate-change actions, bridging social capital between riparian states that share a given basin has been strengthened [17
SSI is essential for diverse out-groups that have a limited history of collaborative actions [40
]. We define diversity as the distribution of demographic attributes (e.g., age, nationality, racio-ethinicty, sex, education level) and underlying personal attributes (e.g., values, cognitive, functional, personality, capabilities, knowledge). Studies confirm that diversity has value [36
]. First to the network of water negotiators representing the riparian states within a given river basin, it spurs creativity and innovation [36
]. Haidt [42
] (p. 2) states that a diverse environment encourages complex thinking, increases performance, participation, motivation to do more than the bare minimum and interest in the subject matter. Where there is inequity, diversity may support the process of removing barriers to achieving equity and addressing past inequities [18
]. Salman [43
] explains how a bilateral water agreement between two downstream countries that share water flows within the river forecloses the future use of the water by the upstream countries. In this instance, diversity may facilitate the removal of the foreclosure barrier and address inequities occasioned by the bilateral agreement.
Jackson, Stone and Alvarez [44
] classify diversity into two groups, namely, personal and demographic attributes. Demographic attributes are defined as “immutable … readily detected during a brief interaction with a person, and for which social consensus can be assumed” [44
] (p. 56). Haidt [42
] (p. 4) provides a list of demographic attributes, namely, sex, age, race, and ethnicity. Jackson et al. [44
] (p. 56) define personal attributes as “mutable and subjectively construed psychological and interpersonal characteristics”. Haidt [42
] (p. 4) provides a list of personal attributes, namely, status, knowledge, behavioral style and values. Haidt [42
] argues that amongst PAD, values (including attitudes) have barely been researched. Kakabadse et al. [45
] (p. 23) affirm the importance of personal attributes, specifically cognitive abilities, values, background and experiences, in influencing decisions.
Previous research has mainly focused on demographic diversity (DD), with limited studies on underlying personal attributes diversity (PAD) [46
]. Jackson [46
] (p.805) identifies the most studied attributes in diversity research. Sex (DD) was the highest studied, followed by age (DD), racio-ethnicity (DD), education level (DD), functional background (PAD), tenure in organisation (DD), tenure in job/team (DD), cognition/mental models (PAD), personality (PAD), education content (DD), cultural values (PAD) and finally nationality (DD). Most of the studies focused on performance outcomes with a small percentage focusing on process and affective outcomes.
] argues that different forms of diversity lead to different effects and a general study on diversity that does not disaggregate it into its attributes may not produce useful policy insights. Kakabadse [45
] concludes that most of the available research is at the conceptual level, with very limited empirical research on the value addition of diversity. Figure 1
contains literature review on DD and PAD studies and their respective added value including the elements that contributed to value-creation [45
]. Most of the studies are at the conceptual level with empirical research limited to studies on: values, cognitive, nationality and age diversity.
According to Figure 1
, gender diversity is the most studied with mixed results on its added value and the contributing elements to value-creation [45
]. From the literature, age, was the least studied, with consistent results. Age contributed to improved decision making by balancing personal drive with caution [55
]. Moreover, older persons were considered an asset because they possessed a broader network that was essential in the decision-making processes [56
]. Ethnicity is critical when: social capital needs to be built; new life experiences or unique social connections are missing in the current network; or influential social personalities are needed [36
]. Nguyen (2015) indicates that increased cognitive ability leads to improved review and probing [55
Functional diversity led to improved decisions and services due to one major element: increased team cognitive ability [45
]. The cognitive results were the most consistent. Cognitive diverse teams made better decisions due to increased team thinking ability [45
]. A value diverse group improves the decisions made due to: increased innovation when working in mixed teams [45
], introduction to unique networks [42
], increased cognitive ability [63
] and the unique life experiences of each team member [64
Demographic diversity is costly, especially in the short-term [36
]. Based on Twigg and Taylor [65
], diversity led to reduced levels of trust and social cohesion. The study mainly looked at demographic diversity (age, ethnicity, income level, education level, occupation, tenure and place of residence) [65
], (p. 1429). De Oliveira and Nisbett [66
] conclude that demographic diversity does not lead to wiser decisions. Putnam [36
] (pp. 149–150,165) adds that demographic, specifically ethnic, diversity triggers anomie and social isolation. He adds, that in the short-term ethnic diversity is negatively correlated with social capital and engagement in cooperative actions. According to Putnam [36
] (p. 149), increased demographic diversity has demonstrated:
Declined confidence in one’s ability to influence the situation and bring about change;
Lesser frequency to participate in democratic processes, with increased interest and political knowledge that is essential for protests;
A lower expectation of cooperation by the opposing team to resolve the collective dilemma; and
Declining interest to participate in joint actions.
There is barely any research on the discriminant power of DD and PAD in a given group [45
]. We conducted this research to address the identified research gap with the aim of reducing the water management costs that arise from heterogeneity, by predicting the possible future group configuration and its strongest diversity attribute. In addition, there is no study that assesses what happens when the heterogeneous groups transform into a demographic homogenous (DH) or a personal attribute homogenous (PAH) group. Do other subdued diversity attributes take prominence and change the group dynamics? The outcomes may guide water resources management experts to emphasize on the most powerful diversity attribute, so as to enhance its benefits, reduce the costs and focus less on attributes that have limited or no impact on the final outcome. Based on the research outcomes, further diversity studies in water resources management can be conducted on how to introduce and strengthen SSI using the most powerful diversity attribute, so that the heterogeneous group enjoys the benefits of diversity and homogeneity (SSI).
Therefore, we hypothesize that PAD is a stronger predictor than DD (age, education level, and gender) of water negotiation outcomes (whether a water negotiation groups will develop SSI surpassing in and out-group differences and cooperate or they will act unilaterally), and will diminish in PAH groups leading to a change in group dynamics as DD takes prominence. With the use of a negotiation game known as Nzoia WeShareIt, we examine seven teams of negotiators from four county governments (Bungoma, Trans Nzoia, Kakamega and Busia) in the western part of Kenya. By analyzing the in-game and post-game data, we assess which, if any, of these four variables, are useful in predicting whether the composition of certain negotiation teams will cooperate or act unilaterally, leading to unhealthy competition for scarce water resources.
We conducted a discriminant analysis (DA) as a grouping and predictive technique, with the pre-game and post-game questionnaire data. First, we maintained the status quo, the players negotiate within an environment where the four variables are under consideration. Afterward, we conducted a follow-up analysis where we excluded PAD, which is the variable with the highest discriminant power. We then assessed the power of the other three variables in predicting whether the negotiation groups will cooperate or unilaterally act. The two instances are compared to assess the discriminating power of PAD and DD (gender, age, and education level).
The remainder of the paper is organized as follows. First, we provide a detailed description of the Nzoia river basin case study, the water negotiation game (Nzoia WeShareIt), the procedure we employed to play the game and collect the research data and how we analyzed the data. The third section discusses the results of the in-game, and post-game questionnaire data. The final section discusses and makes concluding remarks.
4. Discussion and Conclusions
The results confirm the hypothesis that PAD is a better predictor than DD (age, education level, and gender) of negotiation outcomes (whether a water negotiation groups will develop SSI surpassing in and out-group differences and cooperate or they will act unilaterally). The MDA procedure indicate that the strongest predictor of water negotiation outcomes in the Nzoia WeShareIt game is PAD. When assessing the impact on negotiation outcomes in the MDA, a four-structure matrix PAD is the dominant predictor with little or no influence from gender, age and education.
The results also support previous studies indicating that PAD is a stronger predictor of improved decision-making than DD. Based on the reviewed literature, we attribute PAD being the strongest predictor of the water negotiation outcomes to four main factors: increased cognitive ability [45
], innovative decision-making [45
], unique networks [42
], and unique life experiences [64
Moreover, when we eliminated PAD from the model, gender and education gained more prominence and competed almost equally. Thus, when PAD is negligible, for instance a water negotiation team comprising of only lawyers (functional), with similar knowledge, cognitive skills, capabilities and values, then gender and education diversity will take prominence. Since age and gender are negatively correlated, they jointly have a stronger discriminating power than education. The discriminating power of gender is the highest because its correlation coefficient is the highest, followed very closely by education. However, when gender and age are combined, they possess more discriminating power than education.
These second result clearly presents a challenge and possibly an opportunity. Based on previous research, it is important to focus more on PAD rather than DD [42
]. As Putnam state DD “at least in the short run, seems to bring out the turtle in all of us” [36
] (p. 151). However, the results in this paper indicate that when PAH negotiation team is constituted, there is a high likelihood that decisions will be influenced not by PAD (because it no longer exists) but by gender and education level. Moreover, as earlier discussed, the literature on DD is not conclusive. It provides numerous outcomes that could not be easily substantiated since most of the studies on DD were conceptual in nature with no empirical backing. Moreover, DD research indicate that in the short term, DD does not build trust [65
], social cohesion [36
], nor does it lead automatically to improved decision-making [66
]. Research also indicates that DD is useful for monitoring, evaluation, service delivery, broadening the network, tapping into unique networks and fostering equity [45
Therefore, if the aim of the basin management institution is to improve decision making and enhance cooperation, PAH may be a threat to this aim, thereby presenting a challenge. Nevertheless, in such instances, there are two policy options that water policymakers may decide upon, which may open more opportunities for integrated river basin management. First, diversify their PAH negotiation teams by introducing new members who possess divergent values, skills, capabilities, functional, cognitive abilities and knowledge. Second, introduce SSI to develop bonding and bridging social capital that enables the demographic heterogeneous PAH group to surpass their differences, perceive themselves as one team, and be willing to cooperate.
This empirical study, conducted in Kenya, supports the argument that diversity discussions should move away from whether diversity is good or bad towards understanding how the different diversity attributes contribute to cooperative decision-making, their respective elements and their unique value addition. If the policy aim is improved decision-making in water management, then more focus should be on PAD than on DD. However, if the aim is improved supervision, monitoring, evaluation and service delivery, then DD should be the focus when deciding on group composition. In addition, as argued above, there are different types of DD and PAD, each with different influencing power on specific circumstances and outcomes. However, it should be noted that the conclusion regarding the functions of PAD and DD is inferred from the literature review conducted at the beginning of this paper and not directly assessed in this particular study. Therefore, to get more clarity there is a need for further investigations on the contribution of different diversity attributes to negotiation outcomes in a given river basin.
The research approach faced a few limitations. First, the broad assertion that water resource negotiation teams can be ideally formed with attention to the diversity characteristics presented in the paper may be considered is an assumption. Sometimes, the formation of the team is based on the national laws and regulations or other considerations. Moreover, we acknowledge the limitation that the research is based on outcomes of a simulation game and not an actual negotiation. This is one of the major challenges faced by transition management experiments, whether gaming simulation or otherwise. We acknowledge the limitations of the study and propose caution and further analyses in the form of an actual pilot programme before considering scaling up. Nevertheless, gaming simulation has an effective role to play in research and knowledge diffusion. Gaming simulation can be attributed to real life situations through use of a game as a research tool and ensuring a diffusion of knowledge on real world situations. The Nzoia WeShareIt game was entrenched to the ongoing water policy reforms in Kenya to test the efficacy of proposed diversity related water policies in a game environment before actual application in a real-life setting. Another limitation is that the Nzoia WeShareIt game constructed solely intra-county basin management, whereas most of the water negotiations are conducted at the international basin level. The Nzoia WeShareIt game is inspired by the Nile WeShareIt game, which we developed for the Nile basin. The Nzoia river basin is a sub-basin of the Lake Victoria basin and the Nile basin. Considering the complexity and challenges in this sub-basin; and it being the largest tributary to the Lake Victoria basin in Kenya and second largest at the international level after Kagera basin, and also considering the upstream–downstream tensions within this sub-basin, it seems justifiable to use the term basin. We also note that the conclusions and the use of the games as a learning tool for negotiators would have been made much stronger with a meta-game session involving several or all of the county teams. We hope to implement this in future studies to ensure that the results are validated at the basin level by all the county governments.
Clearly there is need for further studies to understand these complexities and provide more guidance to decision-makers on what mix of diversity attributes to focus on, so as to get the intended outcome. Our study concentrated on water negotiations in the Nzoia river basin in Kenya. Our findings, therefore, are valid only for this particular situation, but the implications might be wider. The findings put to discussion the idea that DD rather than PAD characteristics are the best predictor of successful negotiations. Evidently this is not always the case and we are not the first to make this claim explicit. Therefore, at the river basin level, determining the predictors of negotiation outcomes can guide the water policymakers to focus on strengthening the high predictors to get the best outcome out of a planned water negotiation. This information would support or expedite the process of developing cooperative framework agreements aimed at increasing water access and reducing water scarcity.