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neither did it fulfill its concessional obligations, due to what government officers perceived as underperformance. Available data on annual freight and passenger volumes also suggest that the concessionaire was way below performance targets (IEA-Kenya, 2014). The Government and KRC officers linked RVR’s underperformance to lack of financial capacity and technical expertise. This study examined various factors influencing the project’s financing, including macro-economic, concessional, financial, legal and environmental; however, this article focuses on the influence of concessional factors within the Kenyan context.

LITERATURE REVIEW

In many developing countries, governments face the challenge of meeting the growing demand for essential services, including transport, communication and energy, among others, due to financial and capacity constraints. Public-Private Partnership (PPP) initiatives are financing mechanisms that bring together public and private sector operators to develop infrastructural facilities and deliver such services (Asian Development Bank, 2010). Railway transport is one of the services in which governments have involved private sector operators to deliver, through PPP initiatives. A strong PPP system allocates tasks, obligations and risks among public and private partners in an optimal way. Whereas, public partners include government entities, such as ministries, departments, municipalities, or state-owned enterprises, private partners include local or international businesses with technical as well as financial expertise relevant to particular project priorities (Asian Development Bank, 2010).

A review of literature reveals that PPP options vary from one where government retains full responsibility for operations, maintenance, capital, financing and commercial risk; to one in which the private sector takes on much of this responsibility (World Bank, 1997). Based on this premise, PPP options include service contracts, management contracts, leases, concessions and divestitures. In concessions, governments define and grant specific rights to a private operator (concessionaire) to build and operate a facility for a fixed period (United Nations, 2011). Concessions often assume two models, viz. Build-Operate-Transfer (BOT) or Build-Operate-Own (BOO) (Walker, 1993). Although the public authority owns facilities, the private operator has wide-ranging powers over the operation and finances.

The success of concessions depends on the concessionaire’s financial and technical competency.

Concession contracts set out performance targets, including service coverage, quality, standards, arrangements for capital investment, mechanisms for adjusting tariffs, as well as arbitration over disputes (World Bank, 1997). Quite important is that the concessionaire assumes full responsibility for all capital investments required to build, upgrade, or expand facilities. Besides, the concessionaire is responsible for working capital (Asian Development Bank, 2010). The public authority establishes performance standards and ensures compliance. At the end of the contract period, the authority assumes ownership of project facilities and can choose to assume operating responsibility too, renew the operator’s contract, or award a new contract (Asian Development Bank, 2010). Concession contracts often establish tariffs, including provisions for adjustments when need arises. Typical concession periods range between 25 to 30 years, which provide sufficient time for the concessionaire to recover the capital invested and earn sufficient profits.

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 337 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1

DATA AND METHODOLOGY

The study adopted a causal-comparative design and targeted staff of the concessionaire and government authorities. The sampling process identified 402 eligible participants, who were all included in the sample.

We collected primary data in May 2015 after obtaining necessary approval from University of Nairobi, National Council of Science and Technology, as well as KRC. We delivered questionnaires to targeted participants and made follow-ups through e-mails and telephone calls. Of the 402 targeted participants, 348 (86.6%) successfully completed and returned the questionnaires. The analysis involved listing coding, digitalizing and cleaning data for logical inconsistencies and misplaced codes. The methods that we used included descriptive, Chi square tests, one-way analysis of variance (ANOVA) as well as Relative Importance Index (RII) analyses. Kendall’s Coefficient of Concordance enabled us to determine the degree of concordance in participant’s perceptions regarding the influence of concessional factors on the project’s financing. We performed all quantitative analyses using the Statistical Package for Social Sciences and Microsoft Excel. In addition, qualitative analysis involved organizing data under thematic areas, followed by description and thematic analysis to identify emerging themes and patterns (Kometa, Oloimolaiye & Harris, 1994; Frimpong, Olowoye & Crawford, 2003).

RESULTS AND DISCUSSIONS

The results show that of the 348 participants, 134 (38.5%) were staff of KRC; 179 (51.4%) were staff of RVR; 12 (3.4%) were officers of MOF, while 23 (6.6%) served at MOT. By cadre, 109 (31.3%) participants were operational staff, while 39 (11.2%) were managerial staff. Besides, technical staff were 174 (50.0%), monitoring and evaluation staff were 12 (3.4%) while 14 (4.0%) participants served as policy advisory staff at the ministries. The institutions varied significantly in terms of the cadre of staff who participated in the study (χ2 = 251.091, df = 12 and ρ-value = 0.000). In terms of gender, participants included 230 (66.1%) men and 118 (33.9%) women. However, the institutions did not vary significantly in terms participants’ distribution based on gender (χ2 = 1.420, df = 3 and ρ-value = 0.701).





Participants were aged between 22 and 54 years, with the mean age for the entire group being 38.7 (≈39) years. Besides, participants from RVR reported the lowest mean age (38.1 years), while those from MOF reported the highest mean age (43.5 years). Even though results suggest that RVR staff may have been the youngest, one-way analysis of variance (ANOVA) revealed that there was no significant variation among staff of various stakeholders regarding age (F(3, 344) = 1.627 & ρ = 0.183). Besides, participants reported a mean of 16.41 (≈16) years of experience, with the lowest being 1 year and the highest 35 years. Whereas staff of RVR reported the lowest duration of professional experience (15.8 years), the results suggest that the staff of the MOF were the most experience (22.2 years). Based on this, the ANOVA results show lack of a significant variation among staff of various stakeholders regarding years of professional experience (F(3, 344) = 2.255 & ρ-value = 0.102).

Concessional Factors Influencing Financing of the Project

The results presented in Table 1 show that of the 348 participants, 137 (39.4%) believed that lack of regular performance review forums had a ‘very strong’ influence on the project’s financing, while 79 (22.7%) reported that the indicator’s influence on the project’s financing was ‘strong’. Contrastingly, 49 (14.1%) participants indicated that lack of regular performance review forums had a ‘very weak’ influence on the project’s financing, while 30 (8.6%) described the indicator’s influence as ‘weak’. There was a significant variation in perceptions regarding the indicator’s influence on the project’s financing (χ2 = 10.231, df = 12 & ρ-value = 0.083). Regarding concessionaire’s technical capacity, 90 (25.9%) participants described the indicator’s influence on the project’s financing as ‘very strong’, 76 (21.8%) felt that the indicator had a ‘strong’ influence. Those who felt that concessionaire’s technical capacity had a ‘very weak’ influence on GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 338 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 the project’s financing were 66 (19.0%), while those saying that the indicator’s influence was ‘weak’ were 62 (17.8%). The analysis obtained a significant variation in perceptions regarding the influence of concessionaire’s technical capacity on the project’s financing (χ2 = 66.743, df = 12 & ρ-value = 0.000).

The results further show that 70 (20.1%) participants stated that concession fees structure had a ‘very strong’ influence on the project’s financing, while 150 (43.1%) felt that the indicators’ influence was ‘strong’. However, 21 (6.0%) participants were of the view that concession fees structure had a ‘very weak’ influence on the project’s financing, while 40 (11.5%) felt that the indicator’s influence was ‘weak’. The analysis revealed a significant variation in perceptions regarding the influence of concession fees structure on the project’s financing (χ2 = 23.138, df = 12 & ρ-value = 0.027).

Table 1: Perceived Influence of Concessional Factors on the Project’s Financing

–  –  –

Table 1 further shows that 136 (39.1%) participants were of the view that the influence of concessionaire’s revenue on the project’s financing was ‘very strong’, while 120 (34.5%) felt that the indicator’s influence was ‘strong’. Those who perceived that the concessionaire’s influence on the project’s financing was ‘very GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 339 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 weak’ were 20 (5.7%), while those saying the indicator’s influence was ‘weak’ were 24 (6.9%). However, there was no significant variation in perceptions regarding the influence of concessionaire’s revenue on the project’s financing (χ2 = 11.981, df = 12 & ρ-value = 0.447). The results show that 79 (22.6%) participants reported that adjustment of tariffs had a ‘very strong’ influence on the project’s financing as ‘very strong’, while 129 (37.1%) stated that the indicator’s influence was ‘strong’. However, 27 (7.8%) participants perceived that adjustment of tariffs had a ‘very weak’ influence on the project’s financing, while 46 (13.2%) believed that the indicator had a ‘weak’ influence on the project’s financing. There was no significant variation in perceptions regarding the influence of tariff adjustment on the project’s financing (χ2 = 10.405, df = 12 & ρ-value = 0.581). In addition, 122 (35.1%) participants described the influence of concession period on the project’s financing as ‘very strong’, while 107 (30.7%) perceived that the indicator had a ‘strong’ influence. However, 30 (8.6%) participants were of the view that the influence of concession period on the project’s financing was ‘very weak’, while 43 (12.4%) said that the indicator’s influence was ‘weak’. The analysis revealed a significant variation in perceptions regarding the influence of concession period on financing of the concession project (χ2 = 26.177, df = 12 & ρ-value = 0.010).

Relative Importance of Concessional Factors Influencing the Project’s Financing The Relative Importance Index (RII) results show that lack of performance review forums was the most important concessional factor influencing the project’s financing. The indicator scored a relative importance index of 0.7, which suggests that it was a strong predictor of the project’s financing. Participants reported that the concession agreement did not have a provision for joint evaluation forums for partners to review performance and address issues arising. Regular joint evaluation of concessional projects can greatly improve the management of internal and external risk factors preventing such projects from achieving performance targets; thereby, improve chances and ability to mobilize additional financing for capital investments. Concessionaire’s technical capacity scored a relative importance index of 0.6; which suggests that the indicator was an average predictor of the project’s financing. Participants believed that the concessionaire’s lack of technical capacity exacerbated a decline in volumes of freight and passenger services, which affected the level of net returns, investment targets and the project’s creditworthiness.

Prolonged underperformance undermined the concessionaire’s ability to attract funding from international financial institutions. More still, lack of technical capacity and experience to manage the concession project, raises questions regarding rigorousness of the selection process before the Government awarded the concession.

Having scored a relative importance index of 0.6, concession fees had an average influence on the project’s financing and performance. Participants noted that the fixed fee for passenger services was not feasible, considering a significant drop in passenger volumes during the first decade of the concession. Nonetheless, RVR paid the amount regardless of whether or not it met revenue targets. Whereas, fixed concession fees can be feasible in advanced PPP markets, variable fees are suitable for developing markets. In the case of RVR, participants pointed out that fixed concession fees for passenger services was not a good option considering the level of competition exerted by road transport. Concessionaire’s revenue scored a relative importance index of 0.5; thus, suggesting that the indicator was an average predictor of the project’s financing. Revenue is a key indicator of any business venture’s viability for financing consideration.



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