Journal of
Geography and Regional Planning

  • Abbreviation: J. Geogr. Reg. Plann.
  • Language: English
  • ISSN: 2070-1845
  • DOI: 10.5897/JGRP
  • Start Year: 2008
  • Published Articles: 371

Full Length Research Paper

Drivers to energy efficiency development in lighting and air-conditioning systems in manufacturing industries in Ghana for 2018

Jones Lewis Arthur
  • Jones Lewis Arthur
  • Department of Mechanical Engineering, Institute of Distance Learning, KNUST, Kumasi, Ghana.
  • Google Scholar
Josephine Fianu
  • Josephine Fianu
  • Department of Mechanical Engineering, Institute of Distance Learning, KNUST, Kumasi, Ghana.
  • Google Scholar


  •  Received: 24 April 2019
  •  Accepted: 20 June 2019
  •  Published: 31 July 2019

 ABSTRACT

The increase in electricity demand, coupled with drastic deficit in energy generation and depleting conventional energy resources continues to create complex challenges for the energy market in Ghana. But Energy Efficiency (EE) in lighting and air-conditioning has been considered as a green area for reducing energy consumption. The manufacturing sector has been considered as a key area for the implementation of energy efficiency practices. This paper presents a survey to assess the drivers to energy efficiency in lighting and air-conditioning systems from the perspective of two manufacturing industries. Questionnaires were distributed to 260 employees in two manufacturing industries in Ghana. Key informant interviews were carried with four respondents. The impact of employee gender, department of work and job position in mediating the drivers of EE was also assessed using correlation analysis. The results showed that the staff of manufacturing industries sees the availability of information on energy efficiency measures, staff awareness and knowledge and the availability of funds as leading driversto energy efficiency development. Also providing incentives in the form of awards to employees for energy efficiency participation was shown to be effective in the implementation of EE measures.The inferential statistics showed that employees’ gender, department and job position predict the barriers to energy efficiency in the manufacturing industries. However, few of the drivers of energy efficiency are not dependent on gender, department of work and job position.
 
Key words: Energy efficiency, energy consumption, drivers.


 INTRODUCTION

The increase in electricity demand, coupled with drastic deficits in energy generation and depleting conventional energy resources continue to create complex challenges for the energy market in Ghana. Electricity consumption is on a faster rate of rise than other energy vectors due to electrification of energy uses (International Energy Agency, 2017).  Demand  for  electricity  in  Ghana  which has since 2006 to 2016 increased by 52% is challenged by factors including persistent outages (Kemausuor et al., 2011; Gyamfi et al., 2015; Kumi, 2017). The persistent outages are the result of over dependence on the Akosombo Dam, high levels of distribution losses, non-payment of bills, over consumption of energy and a poor tariff  structure  (Energy efficiency (EE) explained  as  the 
more output per unit of input (Patterson, 1996), has emerged as one of the rewarding pathwaysto provide the quickest, cleanest and cheapest and innovativeway to reduce electricity demand (Gellings, 2009). Energy Efficiency (EE) procedures applied in industry include monetary activity such as value addition (Ang and Xu, 2013), and for petrochemical industries they include: decreasing fossil fuel and electricity demand by increasing heat integration within individual processes and across the total cluster site; replacing fossil feedstock with renewable and bio-refinery integration with the existing cluster; and increasing external utilization of excess process heat wherever possible (Hackl and Harvey, 2013). Specifically for lighting and air-conditioning (AC) in industries, EE measures have involved the use of efficient lighting devices, energy labelling of new refrigerators, SWH instead of diesel, gas or electric boilers, high efficient motors, and properly adjusting HV AC and steam boilers to save an average of 15% on energy consumption (Bose, 1992; Mahmoud and Ibrik, 2002; Ibrik and Mahmoud, 2005). Many arguments which cited the need for energy efficiency to provide a win-win opportunity for energy demand-supply matrix do not meet modern standards of credibility and empirical evidence (Allcott and Greenstone, 2012). In Ghana, the energy efficiency concept has to date received little attention (Gyamfi et al., 2018). Programs toward energy efficiency have focused predominantly on the residential and commercial sectors. However, the contribution of industries to the heightening of electricity demand cannot be under-estimated (Owusu, 2010; Energy Commission, 2017). Therefore, exploring an empirical study that examines opportunities for energy efficiency is critical (Allcott and Greenstone, 2012).
 
Electricity usage in industries, lighting and air-conditioners continue to be the major consuming devices of electricity in developing countries like Ghana. It is reported that electricity consumption by cooling using air conditioners in manufacturing industries would offer a potential of 8% savings in Ghana through the proper enforcement of energy efficiency standards (Koizumi, 2007; Gyamfi et al., 2017; Gyamfi et al., 2018). It is therefore a wakeup call to promote energy efficiency measures for optimal electricity usage in lighting and air-conditioners.
 
Efforts to promoteenergy efficiency in lighting and air condition in the industrial sector over the yearshave proved futile because of the lack of understanding on the drivers towards energy efficiency. Many different theoretical approaches to drivers of EE have been advanced in the relevant literature (De Groot et al., 2002; DeCanio, 1998; Trianni et al., 2013). However, few studies exist for drivers of energy efficiency (Cagno et al., 2013), the studies focus on which drivers should be highlighted but not for the decision-making process (Cagno et al., 2014). Some studies have shown that key knowledge of the economic,  behavioural,  organizational, informational and technological-related drivers can help generate initiatives towards energy efficiency as well as harness the full potential of energy efficiency in the manufacturing industries (Spallina and Marchesani, 2012; Apeaning and Thollander, 2013). Kambule (2014) have revealed that gaps between adoption and perception of Energy Efficiency (EE) can be the result of several drivers including shortfalls in finance, human skills, time, training and information. These arguments therefore call for further investigation into possible factors that can mediate drivers to EE. 
 
A number of studies have found gender to mediate pro-environmental attitudes (Kollmus and Agyeman, 2002; Tindall et al., 2003; Gifford and Nilsson, 2014). Kollmuss and Agyeman (2002) in a paper "minding the gap: why do people act...barriers to pro-environmental behaviour" argue that although women have less extensive knowledge than men,women are found to be more emotionally engaged and as a result tend to show more concern in relation to environmental destruction, they believe less in technological solutions, and are more willing to change behaviour. But Gifford and Nilsson (2014) are of the view that gender differences that influence pro-environmental concerns and behaviours fails to work outside the home. In Ghana where gender differences occur for people working in the industrial sector (Amu, 2005; Heintz, 2005; Peprah, 2011), it is important to explore measures to address gender impact differences associated withdrivers ofEE.
 
Other factors having the potential to mediate drivers to EE are the type or department of work. Schleich (2009) in 'an exploration of drivers to energy efficiency' identifies a heterogeneous picture of sector-specific differences in the relevance of the individual drivers of EE. The heterogeneity in the EE differences is independent of an organization's EE performance. Organization, therefore, under-estimates the internal priority setting as a barrier to EE when dealing with planned projects (Schleich, 2009).Linked to an employee's department of work,as predictors of the drivers to EE, is that of the position held by the employee in the industrial sector.
 
The work schedule of an employee in terms of occupancy behaviour, can significantly impact on energy in terms of energy end use levels such as lighting, space cooling and heating (Hong and Lin, 2013). The impact of who occupies a building may be translated as 50% less energy for austerity lifestyle, while the wasteful work style consumes up to 90% more energy. Other studies by Brummelhuis et al. (2012) in 'do new ways of working foster work engagement?' identified that flexible work designs, including those of management and higher level employees allow employees to schedule work to suit the best situation, thereby saving time and energy. It is essential to explore, whether the schedule of employees in the industrial sector in Ghana can predict drivers of EE for lighting and AC 
 
In spite  of  the  many  works  that  have  assessed  the drivers to EE in manufacturing industries, it is interesting to point out that much of the  literature has failed to address the levels of dependence of energy efficiency drivers in the manufacturing sub sector which is critical for understanding the dynamics ofdrivers to energy efficiency. Moreover, there are limited works that address the drivers to EE implementation in lighting and air conditioning in Africa and for that matter Ghana.The paper also explores gaps in the EE literature including whether gender, type/department of work and position in employment can predict the drivers of energy efficiency in lighting and air-conditioning systems in manufacturing industries in Ghana.
 
This work seeks to study the key drivers that influence the implementation and development of energy efficiency practices that drive EE performance in the manufacturing sub sector of Ghana.
 


 MATERIALS AND METHODS

A descriptive design that explored the perceptions of people on key drivers of EE was applied to provide an in-depth investigation into lighting and AC for the manufacturing sub-sector of Ghana. A mix of quantitative and qualitative designs was considered for the study. The quantitative approach was used to gather quantitative data from respondents whilst the qualitative data provided clarifications to the statistical values obtained from the quantitative data. 
 
A population of 774 representing 636 and 138 from a food manufacturing company and cement manufacturing company respectively was used for the study. These companies were selected due to their location, diversity of energy usage, and high production levels that demanded a higher consumption of energy as well as the urgency to ensure energy efficiency. A sample size of 260 was sampled for the study (Twumasi et al., 2017). The distribution of the sample is shown in Table 1.
 
 
A number of sampling frames were applied to the study. These included a purposive frame to pre-select the two companies, a cluster of departmentalization for each company, that is, Engineering and non-Engineering sections of the company and a random sampling approach to select the required number of respondents for each company. Only Straight day workers were asked to complete the questionnaire in order to ease the collection of completed questionnaires whilst heads of the engineering and non-engineering sections of the two industries were purposively selected for the interviews. The survey questions were carefully selected from a review of available literature and pretested for clarity and reliability and into simple and understandable terms. Preliminary studies were performed on five employees to ensureclarity of the questions. The questionnaires highlighted the drivers to energy efficiency. 
 
Questions were categorized into three sections; background description, assessment of motivation measures for employee engagement in energy efficiency and assessment of the drivers to energy efficiency in lighting and air-conditioning systems in manufacturing industries. Background description explores gender, department of work, and position of employees to assess whether those variables can predict the drivers and motivational variables of EE in the two selected industries. Drivers were explored under the same variables because they provided the underlying information on assessment of EE in lighting and air-conditioning systems. Variables considered under drivers therefore included availability of information on EE measures, funds, staff awareness and knowledge, and recognition  of  the  environmental  benefits  of  EE. 
 
Motivational measures available and applicable in these two industries, that is, the two main awards for applying EE were assessed. These were quarterly awards for adopting innovative ideas on EE and quarterly departmental award system for the most EE department.
 
The questionnaires were analyzed using the Statistical Package of Social Science (SPSS) version 21. The Respondents indicated their level of agreement with the statements by basing on a 5-point Likert Scale. Each level on the scale was assigned a code ranging from strongly agree, agree, neither/uncertain, disagree to strongly disagree. The findings were then presented in charts, graphs, and tables using descriptive statistics, frequency analysis tools and the cross-tabulated analysis in order to evaluate the relationship between variables of the data. The chi-square analysis, a non-parametric test, was used to establish the relationship between the variables. This inferential test was then used to understand the relationship between employee's gender, department of work and job position and the various drivers to energy efficiency.
 
An interview guide was used to conduct interviews with key informants from the two industries. The face-to-face interviews used covered respondents representing the engineering and non-engineering sections of the two industries. Questions used for the interview included: what are your thoughts on drivers to EE in lighting and air-conditioning systems in your industry? And what are the motivational tools applicable to EE in lighting and air-conditioning systems in your industry? In all, four (4) interviews were conducted. The transcripts were grouped into themes that directly reflected the objectives of the study. These themes were used to provide clarifications for descriptive statistics obtained from the quantitative data.
 

 


 RESULTS

Demographics of respondents
 
The demographics of respondents are shown in Table 2. The scores indicate a higher (76.7%) representation for males as against female respondents. Department of respondents were categorized under 43.2 % (102) for engineering and 56.8% (134) for non-engineering departments. The majority (52.2%) of respondents are technicians, 39.8% are supervisors and 7.6% are managers.
 
 
 
It is important to note that the higher representation for supervisors and technicians is good for a good assessment of the study variables since these respondents are more knowledgeable about the issues of drivers to energy efficiency and are directly involved in the use, monitoring and maintenance of the equipment in the manufacturing industries. The gender card plays well in favour of males because it is generally assumed that the strenuous nature of work and working conditions in the industrial sector make it more favourable for males than females.
 
Assessment of the drivers to energy efficiency in manufacturing industries
 
Respondents were assessed on the drivers to energy efficiency in the manufacturing industries as indicated under Table 3.
 
The study results show that over 60% of respondents agree that lack of information on EE measures is a key driver of EE as against 20.8% that disagreed. On the issue of fund availability, there was a near split on whether it was a driver or not. Generally, scores for agreement were higher than those who disagree for all aspects of drivers to EE in lighting and air-conditioning in the two industries studied. Mean scores for drivers to energy efficiency showed that respondents agree that the main barrier and driver of EE is lack of funds (mean= 2.99), followed by lack of technical skills (mean=2.86). Key informants indicated that EE policies are good and their companies have good and documented policies for achieving EE; however, the requisite funds to support such innovative ideas are difficult to access in their establishments. Other arguments cited EE policy implementation as creating additional cost implications usually beyond the financial capabilities of their organizations. The least scoring driver to energy efficiency in the manufacturing sector is lack of information in energy efficiency measures (mean= 2.4). Informants agreed that information on EE measures do exist but the cost implication of carrying out such measures prevents the industries from meeting their EE obligations.
 
Assessment of motivation measures for employee engagement in energy efficiency
 
The results show that the majority (82.2%) of respondents agree  that   quarterly   awards   are   given   to   motivate employees who apply innovative ideas on EE (Table 4).  This development is also evident for departments that excel as the most energy efficient department. It came out that issuing quarterly departmental awards for most energy efficient departments (mean=1.89) was the more popular option than that of providing quarterly awards for innovative ideas on energy efficiency (mean=1.85). This shows that respondents are more interested in the direct benefit of ensuring energy efficiency in the departments within the organization.
 
Correlation analysis
 
Drivers to energy efficiency measures by gender of respondents
 
Table 5 explores the relationship between the drivers to energy efficiency and gender of employees. Generally, males performed better where gender was a deciding factor in mediating drivers to EE in lighting air-conditioning industries in Ghana, except for recognition of environmental benefits of EE where women performed better than males (Table 5). This development can be attributed to the fact that the number of females working in the selected industries and the industrial section in general are skewed with respect tomales. This scenario is essentially worse when it comes to the engineering and non-engineering sectors of industries where males also males also dominate for engineering.
 
 
Scores on  correlation  showed  that most of the drivers  dependent on the employee’s gender, only drivers such as the availability of funds and staff awareness and knowledge were not related to the employee’s gender. Key informants argued that the majority of the non-engineering staff are women who spend most of the working hours in the office and therefore women become the major beneficiaries of the use of lighting and air-conditioning in the industrial sector. It therefore speaks to the fact that any major decision to improve   EE    in   the   industrial   sector   will be successful if gender becomes a conduit.
 
Comparison of the drivers to energy efficiency measures by employees’ department
 
Table 6 shows the relationship between drivers to energy efficiency and employee's department. The scores show that non-engineering performed better than engineering for all aspects of the drivers.   This      result    also     supports    earlier submissions indicating that the department of work is gender sensitive; and is skewed towards more females in non-engineering sections. These respondents in the non-engineering departments represent a larger number of people who conduct their work in offices where lighting and air-conditioning are most evident. The department of the employee was revealed to be highly dependent on all variables under drivers and challenges to energy efficiency in lighting and air-conditioning except for recognition of environmental benefits which was not significantly related. Department of work does not predict recognition to environmental benefits because this variable is strongly represented by people in the non-engineering sections who are mainly females.
 
Relationship between drivers to energy efficiency and job position of employees
 
Table 7 shows the relationship between drivers to energy efficiency and employees ’job positions. The score for whether position can predict drivers to  lighting  and  air-conditioning  for  the  selected industries showed that managers performed better for all aspects of drivers to EE (Table 7). Scores for supervisors were also better than the technician for all aspects of drivers of EE for lighting and air-conditioning. The worst performing predictor variable under position was technician. Key informant interviews suggested that the trend in the scores is a reality since managers are policy makers, implementers and evaluators and are therefore highly rated in ensuring that the integrity of EE policies are adhered to in the establishment.
 
The analysis showed mixed results for whether position can predict drivers to energy efficiency for lighting and air-conditioning for the selected industries. Position of employees predicted all aspects of drivers of EE except for availability of information in EE measures and staff awareness and knowledge on EE.
 
 
 

 


 DISCUSSIONS

Issues of Energy Efficiency in lighting and air-conditioning (AC) have become an area of increased interest for many industries due to the potential contribution it can have on efforts to meet  the   energy  demands  of  the  sector.  This research examined drivers and drivers to EE in lighting and AC for selected industries, as well as exploring factors that can mediate these drivers. . Drivers of energy efficiency (EE) in lighting and AC in the manufacturing industry are rated from highest for availability of funds, then availability of technical skills, recognition to environmental benefits, awareness and knowledge on EE measures to the lowest, information on energy efficiency measures.The issue of non-availability of funds is highly rated due to its centrality in contributing to all the other drivers to support EE Although policydocuments and guidelines for applying EE are available, the non-availability of requisite funds prevents its implementation in many cases.The results support the available literature (Spallina and Marchesani, 2012; Apeaning and Thollander, 2013; Kambule, 2014; Ang and Xu, 2013) suggesting the centrality of funds availability as the main variable driving EE efforts in lighting and AC for manufacturing industries. Not-withstanding, this literature also emphasizes the important roles played by access to time, training, and relevant information in the drive to EE in the industrial sector.
 
Innovative measures applied by the manufacturing industries to encourage EE is mainly the institution of quarterly awards for employees that apply innovative ideas on EE followed by the application of quarterly departmental award systems to motivate workers towards EE. Provision of tangible motivational packages to staff for implementing EE measures, have the potential to yield more results. The approach to motivating staff that apply EE speaks to relevant literature in the sense that although it is generally agreed that EE provides a win-win opportunity for energy demand-supply matrix (Allcott and Greenstone, 2012), EE has received less attention in Ghana (Gyamfi et al., 2018) possibly because the motivation for its acceptance and application as applicable in this study has been low.
 
This study confirmed that gender plays key roles in mediating drivers of EE for availability of information on EE measures, availability of technical skills and recognition to the environmental benefits of EE but not for availability of funds and staff awareness and knowledge. Males were significantly better than females in predicting the drivers of EE in lighting and AC for the manufacturing industries except under recognition to environmental benefits where females performed better. Although women form the larger representation of the non-engineering staff who incidentally are mostly office staff that also spend hours of the day using lights and AC, it is significant to note that females performed worst in mediating many of the drivers to EE. The study results positively relate to Kollmuss and Agyeman (2002)'s paper of 'minding the gap: why do people act...drivers to ‘pro-environmental behaviour' who argued that  women have better concern than men for environmental destruction, as well as being more willing to change behaviour including towards EE. Comparing the study results to Peprah (2011) shows a  differing  outcome  since  Peprah argued that gender and for this case women's mediated actions of EE are limited to the home rather than to the industrial settings.
 
The departments as well as job schedule of employees were identified to provide different results for the drivers to EE. Generally, the department of work was a significant factor mediating all aspects of drivers of EE in lighting and AC in manufacturing industries except for recognition of environmental benefits of EE. Meanwhile staff in the non-engineering sections of manufacturing industries perform better that those of their colleagues in the engineering section. The test for EE application will therefore provide some variability to the type of schedule an employee is assigned to in the industrial section. This is supported by the fact that the larger number of staff in the non-engineering section who incidentally are mostly females will predict EE policies and application since they are also in the offices where lighting and ACs are mostly used. To achieve success in EE policy implementation in the manufacturing industries, particular attention should be paid to the department of work of employees since the department of work can mediate drivers of EE in lighting and AC. The study further gives a boost  to Schleich (2009) who explored barriers to EE and identified that a heterogeneous picture of sector-specific differences in the relevance of drivers to EE was evident, especially where the type of work performed in the industrial sector is to be considered as variable to explore the implementation of EE.
 
The roles assigned employees have the strength to mediate EE for lack of funds, technical skills and recognition to environmental benefits for the industrial sector. Issues of lack of information on EE measures, and staff awareness are on the other hand not affected by the positions of employees when their EE consciousness is assessed. In the study, managers performed better than supervisors and then technicians for all aspects of the drivers of EE in lighting and AC in manufacturing industries. The trend is a reflection of the critical roles such as policy formulation, implementation and monitoring mainly executed by managers rather than supervisors and technicians in the manufacturing industries. The results corroborates the findings of Hong and Lin (2013) that explored employee occupancy behaviour and found that the role of employees occupying building in industries can mediate energy use levels for lighting, space cooling and heating. The result is significantly related to Brummelhuis et al. (2012) who also identified that work schedule relating to managerial or supervisory roles can allow for flexible work designs to suit situations that positively impact on EE.

 


 CONCLUSIONS

The research explored knowledge on the drivers to energy efficiency development in lighting and air- conditioning systems  in manufacturing industries through the lens of two manufacturing industries in Ghana. The main driver of EE in lighting and AC for manufacturing industries is availability of funds to support EE policies. Other factors also driving EE range from availability of technical skills, recognition to environmental benefits, awareness and knowledge on EE measures and information on energy efficiency measures availability of information on energy efficiency measures, staff awareness and knowledge on EE measures and availability of funds as leading drivers to energy efficiency development. Policy implementers of EE should do what is necessary by providing the needed resources to support EE in lighting and AC in the manufacturing sectors since funds availability will go a long way in helping to assemble the other relevant drivers of EE. Innovative measures such as the award schemes should be channeled into EE activities since tangible motivational tools such as instituting awards for applying innovative ideas on EE as well as applying departmental awards for EE can go a long way to make efforts at promoting EE activities in lighting and AC for manufacturing industries a success.
 
Also, the inferential statistics showed that employees’ gender, department and job position affect the barriers to energy efficiency in the manufacturing industries; however few of the drivers on energy efficiency were not dependent on gender, department of work and job position. Males are better predictors of drivers of EE than females except for recognition to environmental benefits. It is also important to note that EE policies in lighting and AC should mostly target females who are known to form a larger representation of non-engineering staff who incidentally are also located in the offices and extensively make use of lights and AC. EE policies should also concentrate on supervisors and technicians rather than managers since supervisors and technicians are weaker predictors of drivers of EE in lighting and AC for manufacturing industries.


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interest.

 



 REFERENCES

Allcott H Greenstone M (2012). Is there an energy efficiency gap?. Journal of Economic Perspectives 26(1):3-28. 
Crossref

 

Amu NJ (2005). The role of women in Ghana's economy. Friedrich Ebert Foundation. Available at: 

View

 
 

Ang BW, Xu XY (2013). Tracking industrial energy efficiency trends using index decomposition analysis. Energy Economics 40:1014-1021.
Crossref

 
 

Apeaning RW, Thollander P (2013). Barriers to and driving forces for industrial energy efficiency improvements in African industries-a case study of Ghana's largest industrial area. Journal of Cleaner Production 53:204-213.
Crossref

 
 

Bose BK (1992). Modern Power Electronics Evolution, Technology and Applications. IEEE Press, New York, ISBN 0-87942-282-3.

 
 

Brummelhuis T, Lieke L, Bakker AB (2012). A resource perspective on the work-home Interface: The work-home resources model. American Psychologist 67(7):545.
Crossref

 
 

Cagno E, Trianni A, Spallina G, Marchesani F (2013). Drivers for industrial energy efficiency: pieces of evidence from Italian manufacturing enterprises. In ICAE - International Conference on Applied Energy pp. 1-10.
Crossref

 
 

Cagno E, Trianni A, Worrell E, Miggiano F (2014). Barriers and drivers for energy efficiency: different perspectives from an exploratory study in the Netherlands. Energy Procedia 61:1256-1260.
Crossref

 
 

De Groot H, Verhoef E, Nijkamp P (2001). Energy saving by firms: Decision-making, barriers and policies. Energy Economics 23(6):717-740.
Crossref

 
 

DeCanio SJ (1998). The efficiency paradox: bureaucratic and organizational barriers to profitable energy-saving investments. Energy Policy 26(5):441-454.
Crossref

 
 

Energy Commission (2017). 2017 Energy (Supply and Demand) Outlook for Ghana. Accra: Energy Commission.

 
 

Gellings CW (2009). The smart grid: enabling energy efficiency and demand response. The Fairmont Press, Inc.

 
 

Gifford R, Nilsson A (2014). Personal and social factors that influence pro‐environmental concern and behaviour: A review. International Journal of Psychology 49(3):141-157.
Crossref

 
 

Gyamfi S, Diawuo FA, Kumi EN, Sika F, Modjinou M (2017). The energy efficiency situation in Ghana. Renewable and Sustainable Energy Reviews (School of engineering, University of Energy and Natural Resources).
Crossref

 
 

Gyamfi S, Diawuo FA, Kumi EN, Sika F, Modjinou M (2018). The energy efficiency situation in Ghana. Renewable and Sustainable Energy Reviews 82:1415-1423.
Crossref

 
 

Gyamfi S, Modjinou M, Djordjevic S (2015). Improving electricity supply security in Ghana-The potential of renewable energy. Renewable and Sustainable Energy Reviews 43:1035-1045.
Crossref

 
 

Hackl R, Harvey S (2013). Framework methodology for increased energy efficiency and renewable feedstock integration in industrial clusters. Applied Energy 112:1500-1509.
Crossref

 
 

Heintz J (2005). Employment, poverty, and gender in Ghana. Available at: 

View

 
 

Hong T, Lin HW (2013). Occupant behavior: impact on energy use of private offices (No. LBNL-6128E). Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States).

 
 

Ibrik IH, Mahmoud MM (2005). Energy efficiency improvement procedures and audit results of electrical, thermal and solar applications in Palestine. Energy Policy 33(5):651-658.
Crossref

 
 

International Energy Agency (2017). 'Market Report Series: Energy Efficiency 2017'. P 135 View.

 
 

Kambule N (2014). A survey on the state of energy efficiency adoption and related challenges amongst selected manufacturing SMMEs in the Booysens area of Johannesburg (Doctoral dissertation, University of Johannesburg).

 
 

Kemausuor F, Obeng GY, Brew-Hammond A, Duker A (2011). A review of trends, policies and plans for increasing energy access in Ghana. Renewable and Sustainable Energy Reviews 15(9):5143-5154.
Crossref

 
 

Koizumi S (2007). Energy Efficiency of air conditioners in developing countries and the role of CDM. Paris: International Energy Agency.

 
 

Kollmuss A, Agyeman J (2002). Mind the gap: why do people act environmentally and what are the barriers to pro-environmental behavior?. Environmental Education Research 8(3):239-260.
Crossref

 
 

Kumi EN (2017). The Electricity Situation in Ghana: Challenges and Opportunities. Center for Global Development.

 
 

Mahmoud M, Ibrik I (2002). Power losses reduction in low voltagedistribution networks by improving the power factor in residential sector. Pakistan Journal of Applied Sciences 2(7):727-732.
Crossref

 
 

Malama A, Makashini L, Abanda H, Ng'ombe A, Mudenda PA (2015). A Comparative Analysis of Energy Usage and Energy Efficiency Behavior in Low-and High-Income Households: The Case of Kitwe, Zambia. Resources 4(4):871-902.
Crossref

 
 

Owusu A (2010). Towards a reliable and sustainable source of electricity for micro and small scale light industries in the Kumasi Metropolis (Doctoral dissertation).

 
 

Patterson MG (1996). What is energy efficiency?: Concepts, indicators and methodological issues. Energy Policy 24(5):377-390.
Crossref

 
 

Peprah JA (2011). Women, livelihood and oil and gas discovery in Ghana: An exploratory study of Cape Three Points and surrounding communities. Journal of Sustainable Development 4(3):185.
Crossref

 
 

Schleich J (2009). Barriers to energy efficiency: A comparison across the German commercial and services sector. Ecological Economics 68(7):2150-2159.
Crossref

 
 

Spallina G, Marchesani F (2012). Drivers for industrial energy efficiency: an innovative framework (Anno Accademico 2011-2012). Available at: 

View

 
 

Tindall DB, Davies S, Mauboules C (2003). Activism and conservation behavior in an environmental movement: The contradictory effects of gender. Society and Natural Resources 16(10):909-932.
Crossref

 
 

Trianni A, Cagno E, Worrell E (2013). Innovation and adoption of energy efficient technologies: An exploratory analysis of Italian primary metal manufacturing SMEs. Energy Policy 61:430-440.
Crossref

 
 

Twumasi E, Frimpong EA, Kemausuor F, Appiah DO, Okyere PY (2017). Energy efficiency awareness and preparedness among students. In Power Africa, 2017 IEEE PES. pp. 456-461.
Crossref

 

 




          */?>