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A decision support system for evaluating local authority housing maintenance strategies in the United Kingdom

机译:决策支持系统,用于评估英国的地方政府房屋维护策略

摘要

PurposeudThe lack of smart resources management and servicescape strategies within the social housing sector in the late 1970s influenced the rise of successive Governments to consider the restructuring of the traditional ‘cumbersome’ Local Authority based structures and approaches toward more ‘enterprise focussed’ management organisations (Sharp & Jones 2012). This change in central Government policy encouraged Local Authorities to assign through outsourcing their housing stock (including associated asset management services) as part of a Large Scale Voluntary Transfer (LSVT) via a process of compulsory competitive tendering to Housing Associations and / or set up Housing Trusts to increase the accountability, efficiency, and effectiveness of social housing and healthcare provision in the local community. As part of this modernisation process, all social housing and community care providers (also known as ‘Registered Social Landlords’ - RSLs) became subject to statutory audits, inspections and regulation, and performance management, to ensure the service quality delivery requirements. More recently, however, changes in the legislative framework have introduced choice-based letting policy, putting the customer first, service delivery and additionally RSLs are required to act as ‘Corporate Social Landlords’. These changes have focused RSLs attention on the need to sharpen service responsiveness, especially in the area of housing maintenance management (DETR 2000).ududPrevious research (Holmes 1985; Spedding 1990; Johnston 1993; Stewart & Stoker 1995; Olubodun 1996, 2000, 2001; Sagoo et al. 1996; El-Haram & Horner 2002; Kangwa & Olubodun 2003, 2005; Boussabaine & Kirkham 2004; Jones & Cooper 2007; Prowle 2009; Babangida et al. 2012) has mainly concentrated on analysing maintenance management factors at the micro level; developing maintenance models and framework design for operational level. However, in the social housing sector, there have been no studies undertaken to date that have been focused on housing maintenance strategies – for example, how this is formulated, the key drivers of change and the impact on customer orientated service delivery. The purpose of this study is to identify the critical factors that drive the decision-making process in order to formulate responsive housing maintenance strategies and to develop a decision support model to improve customer service delivery of social housing provision.udResearch methodologyudThrough a process of qualitative case study, pilot questionnaire surveys, workshops and qualitative in-depth interviews, the research has identified how the housing maintenance strategies are formulated and how social housing providers could enhance customer service delivery. The study comprised four phases in order to reflect the key objectives of the research. The first phase comprised a review of literature on social housing provision in the UK, identifying relevant changes in the legislative framework, an assessment of the challenges faced by RSLs and the key factors influencing performance of social housing provision. This phase also included undertaking a case study based on five different RSLs to examine the ‘real problems’ as to how and to what extent RSLs have adopted their organisation in order to meet the changes and challenges which they now face. The second phase investigated the key service factors impacting on housing maintenance strategy design and development through the use of a pilot study questionnaire directed to the asset managers (participating in the survey) and also included a selection of end users of the services (tenants). This phase identified the differences between the perceptions of service providers and the expectations of the service users. A key feature of this phase entailed conducting a workshop to disseminate findings of the pilot study. The workshop also formed a basis for ‘in-depth’ discussions for identifying the key factors, their descriptions, their interactions with each other, their inter-relationships with the tenant type, and their combined impact on formulating responsive housing maintenance strategy. The third phase of the study entailed eliciting qualitative data from the participants using the Repertory Grid (RG) ‘in-depth’ interview technique - a psychology tool in order to gain a deeper understanding of the core important ‘constructs’ and sub-constructs, their characteristics, their inter-relationships in the design and development of effective housing asset maintenance strategies. The fourth phase of this study entailed the development of a decision support system and the qualitative validation of the relationships found to exist between the constructs examined in phase three together with the testing of the model over a period of two months with four of the participating social housing providers.ududFindingsudThe key findings arising from this research suggest that the design and development of value for money maintenance strategies within the public housing sector, are not solely based on physical factors related to the age, condition, location, construction type for example, but rather it was found that the majority of the asset management decisions made, were dependent upon a multivariate of key factors. The study identified 52 key factors, which when grouped together formed seven key cluster (Customer risk factors, Asset manager risk factors, Tenancy risk factors, Neighbourhood and community sustainability risk factors, Financial and economic risk factors, continuous service improvement risk factors and corporate risk factors) which are both ‘unique’ and ‘novel’ and are identified as having a direct influence on the formulation of housing maintenance strategy. These factors should not be considered in isolation and are more akin to the business success factors. The business ‘Balanced Scorecard’ (BSC) was evaluated and used as the basis for a ‘best fit’ model which was tested against four RSL to confirm its validity and its appropriateness. The responses obtained from these trials has indicated that the BSC provides a working tool capable of enhancing RSL organisational capabilities and service delivery effectiveness but also able to incorporate customer views regarding service delivery.ududThis research makes major contributions to the existing limited pool of knowledge relating to strategic asset management within social housing sector and in addition, provides an insight into how housing maintenance strategy can be developed to incorporate feedback from customers (tenants) regarding the quality and responsive service delivery. The research also demonstrates the potential value of the BSC approach to the management tool capable of generating a competitive edge in line with government policy which is currently directed towards encouraging RSLs to adopt a commercial business approach to their operations. The research also demonstrates that the adoption of a decision support system in the form of BSC has the potential to provide useful assistance to RSLs intending to move away from the traditional public sector approaches to management (a more private sector orientated) approach to their operations. The research also shows that asset managers experience little difficulty in understanding the principles behind the BSC approach and its application. In addition, the cascading effect of BSC in housing maintenance strategy means that the strategy can be converted into measurable actions at the operational levels thereby providing a direct link between strategy and its implementation. Due to the absence of suitable benchmarking data, score rating derived from the RG were adopted by asset managers. This approach was found to be highly sensitive in assessing service delivery constructs. Furthermore, the research revealed that the individual constructs (52 key factors) had a profound influence in relation to the strategy formation and the assessment of customer service delivery. The study found that RSLs need to develop a deeper understanding and awareness of their customers concerns in that these factors may have a major impact in the development of a responsive housing maintenance strategy and overall improvements on RSLs performance. A close link was found between customer profile, their financial standing and their service expectations, patterns of behaviour and their interaction with their RSLs. High performance expectation was found on the part of affordable customers, presumably reflecting a higher level of social and economic dependency within this group and greater need for access to services thereby challenging RSLs to deliver higher standards of performance including housing maintenance provision. Other customer groups were noted as placing demand on their RSLs to adopt more holistic approach to formulation of housing maintenance strategy and embrace business-like approach to service delivery in order to facilitate a smooth transition from traditional public sector ethos to one closely akin to that associated with the private sector organisation.ududPractical implicationsudThe practical implications of this research are, that, if RSLs are to meet the demands of complying with a changed legislative framework, deliver responsive housing maintenance services to reflect the ever-changing customer expectations, and to adopt commercial approaches to the development of housing maintenance strategies, RSLs will need to re-engineer their business processes if the demands are to be satisfactorily accommodated. RSLs must also be prepared to adopt ‘smart business’ practices in the future, given that existing Key Line Of Enquiry (KLOEs) approaches now provide an inadequate tool for assessing performance in housing asset management nor are KLOEs sufficiently robust or possessing a sufficient degree of agility for modelling complex service delivery scenarios. As a result of this research, the BSC model has demonstrated its usefulness and its appropriateness to housing maintenance decision making within the current economic conditions and changed regulatory regime. The BSC model is simple in nature but nonetheless sufficiently flexible to allow factors to be added or omitted to accommodate the requirements and structures of individual RSLs.ududAcademic implicationsudTo date, most housing asset management have concentrated on the technical and cost aspects of maintenance management aimed at the micro level and have attached little attention to the needs of strategic management or the potential significance of the customer. These earlier researches have limited application to the needs of strategy management particularly under the current conditions which social housing providers are now required to operate (Sharp & Jones 2012). This study is first of its kind to attempt to evaluate housing maintenance strategy giving considerations to end user ‘the customer’ dimension in service delivery within the social housing sector. ududThis study has adopted a novel approach to this area of research by employing a technique frequently encountered in clinical psychology, based upon the use of a Repertory Grid – a qualitative tool for triadic elicitation of key drivers with a view to providing a robust tool for assisting housing asset managers involved in the development of housing maintenance strategy. The RG personal interviews with senior asset managers revealed hidden and latent factors, which would not have been easily identified had a quantitative questionnaire been used. The hidden constructs which were identified as a result of the applications of this technique are considered to be ‘akin’ to business success factors.ududOriginalityudThis study is also unique in that it has given particular considerations to the provision of housing maintenance service as perceived from the view point of the end users rather than directing itself to the constructional and technical aspects of housing asset management. Also, the research recognises the need for asset managers to become more aware of the implications of social factors and the need for these aspects to be incorporated into strategic maintenance models. A further unique aspect of this research is that it has endeavoured to obtain an insight into the cognitive processes (mind mapping and analytical mental processes) behind the decision making of asset management, in order to identify and understand the nature of the drivers behind these processes to develop a rational decision support model for assisting in the rational formulating of housing maintenance strategy.ududKEYWORDS udSocial Housing, Registered Social Landlords, Social Housing Providers, Customer Service Delivery, Asset Managers, Customer, Tenants, Repertory Grid
机译:目的 ud在1970年代后期,社会住房领域缺乏明智的资源管理和服务环境战略,这影响了历届政府的兴起,他们开始考虑对传统的“繁琐”的地方政府架构进行重组,并采取更多以“企业为中心”的管理组织(Sharp&Jones 2012)。中央政府政策的这种变化鼓励地方当局通过对房屋协会的强制性竞争招标和/或建立房屋的过程,通过将其房屋存量(包括相关的资产管理服务)外包作为大规模自愿转移(LSVT)的一部分进行分配。信托可以提高当地社区对社会住房和医疗保健的问责制,效率和有效性。作为现代化过程的一部分,所有社会住房和社区护理提供者(也称为“注册社会房东”-RSL)都受到法定审核,检查和监管以及绩效管理,以确保提供服务质量。然而,最近,立法框架的变化引入了基于选择的租赁政策,将客户放在第一位,提供服务,另外还要求RSL充当“企业社会房东”。这些变化使RSL将注意力集中在提高服务响应性的需求上,特别是在房屋维护管理领域(DETR 2000)。 ud ud以前的研究(Holmes 1985; Spedding 1990; Johnston 1993; Stewart&Stoker 1995; Olubodun 1996, 2000,2001; Sagoo等1996; El-Haram&Horner 2002; Kangwa&Olubodun 2003,2005; Boussabaine&Kirkham 2004; Jones&Cooper 2007; Prowle 2009; Babangida等2012)主要集中于分析维护管理微观因素;为运营级别开发维护模型和框架设计。但是,在社会住房领域,迄今为止,尚未进行任何针对住房维护策略的研究,例如,如何制定住房维护策略,变革的主要驱动力以及对以客户为导向的服务交付的影响。这项研究的目的是确定驱动决策过程的关键因素,以便制定响应性的住房维护策略并开发决策支持模型,以改善社会住房供应的客户服务交付。通过定性案例研究,试点问卷调查,讲习班和定性深入访谈,研究确定了住房维护策略的制定方式以及社会住房提供商如何提高客户服务水平。该研究包括四个阶段,以反映研究的主要目标。第一阶段包括对英国社会住房供应文献的审查,确定立法框架的相关变化,评估RSL面临的挑战以及影响社会住房供应绩效的关键因素。该阶段还包括根据五个不同的RSL进行案例研究,以检查“实际问题”,以了解RSL如何采用以及在何种程度上采用了他们的组织,以应对他们现在面临的变化和挑战。第二阶段通过使用针对资产管理者(参与调查)的试点研究问卷调查了影响住房维护策略设计和开发的关键服务因素,还包括选择服务的最终用户(租户)。此阶段确定了服务提供商的看法与服务用户的期望之间的差异。该阶段的关键特征是举办研讨会以传播试验研究的结果。该研讨会还为“深入”讨论奠定了基础,以识别关键因素,它们的描述,它们之间的相互作用,它们与租户类型的相互关系以及它们对制定响应性住房维护策略的综合影响。研究的第三阶段需要使用话剧网格(RG)的“深度”访谈技术从参与者那里获取定性数据,这是一种心理学工具,目的是为了更深入地了解核心的重要“结构”和子结构,他们的特点,它们在设计和开发有效的住房资产维护策略中的相互关系。这项研究的第四阶段需要开发决策支持系统,并对第三阶段中检验的构造之间存在的关系进行定性验证,并在两个月内对四个参与的社交网络进行模型测试。 ud udFindings ud这项研究得出的主要结论表明,公共住房部门内物有所值的策略的设计和开发,并非仅基于与年龄,状况,位置,建筑有关的物理因素例如,但实际上发现,大多数资产管理决策均取决于多种关键因素。该研究确定了52个关键因素,将它们组合在一起就形成了七个关键类别(客户风险因素,资产管理者风险因素,租赁风险因素,邻里和社区可持续性风险因素,财务和经济风险因素,持续服务改进风险因素和企业风险)因素),既是“独特的”又是“新颖的”,被认为对住房维护策略的制定具有直接影响。这些因素不应孤立地考虑,而应更类似于业务成功因素。对业务“平衡计分卡”(BSC)进行了评估,并将其用作“最佳拟合”模型的基础,该模型针对四个RSL进行了测试,以确认其有效性和适当性。从这些试验中获得的反馈表明,BSC提供了一种工作工具,既可以增强RSL的组织能力和服务交付效率,又可以纳入客户对服务交付的看法。 ud ud这项研究为现有的有限服务群体做出了重大贡献与社会住房领域的战略资产管理相关的知识,此外,还提供了有关如何制定住房维护策略以结合客户(租户)有关质量和快速响应服务的反馈的见解。该研究还证明了BSC方法对管理工具的潜在价值,该工具能够根据政府政策制定竞争优势,而政府政策目前旨在鼓励RSL在其业务中采用商业方法。研究还表明,采用平衡计分卡形式的决策支持系统有可能为那些打算从传统的公共部门管理方式转向管理(更面向私营部门)方法的RSL提供有用的帮助。研究还表明,资产管理者在理解BSC方法及其应用背后的原理方面几乎没有困难。此外,平衡计分卡在住房维护策略中的级联作用意味着该策略可以在运营级别转换为可衡量的行动,从而在策略与其实施之间提供直接联系。由于缺乏合适的基准数据,资产管理人采用了RG得出的评分等级。发现该方法在评估服务交付结构时非常敏感。此外,研究表明,个体结构(52个关键因素)对战略形成和客户服务交付评估具有深远的影响。该研究发现,RSL需要加深对客户关注点的理解和认识,因为这些因素可能会对响应式住房维护策略的开发和RSL性能的整体改善产生重大影响。在客户档案,财务状况和服务期望,行为模式以及与RSL的交互之间发现了紧密的联系。负担得起的客户对性能的期望很高,这大概反映了该群体中较高的社会和经济依赖性,以及对获得服务的更大需求,从而对RSL提出更高的性能标准(包括住房维护)提出了挑战。注意到其他客户群体对RSL提出了要求,要求他们采用更全面的方法来制定住房维护策略,并采用类似业务的方法来提供服务,以促进从传统公共部门精神向与之类似的平稳过渡。 ud ud的实际影响 ud本研究的实际含义是,如果RSL要满足遵守变更后的立法框架的要求,则提供响应迅速的住房维护服务以反映不断变化的客户期望,并且要采用商业方法来制定住房维护策略,如果要满意地满足需求,RSL将需要重新设计其业务流程。鉴于现有的关键咨询点(KLOE)方法现在提供的住房资产管理绩效评估工具不足,RSO还不准备在将来采用“智能业务”做法,而KLOE也不足够稳健或拥有足够的信用等级。建模复杂服务交付场景的敏捷性。这项研究的结果是,BSC模型已经证明了其在当前经济条件和变化的监管体制下对房屋维修决策的有用性和适用性。 BSC模型本质上很简单,但是仍然足够灵活,可以添加或省略一些因素以适应各个RSL的要求和结构。 ud ud学术意义 ud迄今为止,大多数住房资产管理都集中在技术和成本方面面向微观层面的维护管理,很少关注战略管理的需求或客户的潜在重要性。这些较早的研究在战略管理需求方面的应用有限,特别是在目前要求社会住房提供者运营的当前条件下(Sharp&Jones 2012)。这项研究是尝试评估住房维护策略的同类研究,其中考虑了社会住房部门在提供服务时最终用户的“客户”维度。 ud ud这项研究采用了临床心理学中经常遇到的一种技术,采用了一种新颖的方法来研究这一领域,该技术是基于Repertory Grid的使用的。RepertoryGrid是用于三重启发关键驾驶员的定性工具,目的是提供强大的功能协助住房资产管理人员参与制定住房维护策略的工具。 RG对高级资产管理人的个人访谈揭示了隐藏和潜在的因素,如果使用定量问卷调查,这些因素将不容易发现。由于使用此技术而被识别出的隐藏结构被认为是与业务成功因素“类似”的。 ud ud原创性 ud这项研究的独特之处还在于它特别考虑了住房维护的提供。从最终用户的角度来看服务,而不是直接针对住房资产管理的结构和技术方面。此外,研究还认识到资产经理需要更加意识到社会因素的影响,并且需要将这些方面纳入战略维护模型。这项研究的另一个独特方面是,它努力了解资产管理决策背后的认知过程(思维导图和分析性心理过程),以便识别和理解这些过程背后的驱动因素的性质。 ud ud关键字 ud社会住房,注册社会房东,社会住房提供者,客户服务交付,资产管理人,客户,租户,储备格,以开发合理的决策支持模型来协助合理制定住房维护策略。

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    Sagoo Amritpal S.;

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  • 年度 2014
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