Investigating the deployment of electronic customer relationship management readiness and maturity models in the Iranian banking industry

Customer Relationship Management (CRM) is one of the main priorities for almost all organisations, particularly in the banking world. However, Information technology (IT) has changed ways of interacting with customers, resulting in the appearance of the concept of Electronic Customer Relationship Management (eCRM), which has caused a shift from offline CRM to eCRM. ECRM aims to attract and retain customers (especially valuable ones), to improve customer service by creating a strong relationship with them, and to provide the required financial product at the right time. Thus, it is vital to identify readiness factors in any organisation to prevent eCRM failure. Due to the current gap in the eCRM readiness and maturity assessment area in banks, this research attempts to fill this gap by developing a conceptual framework for eCRM readiness/maturity and accordingly create a tool for banks to assess their eCRM readiness and maturity. This tool helps banks to prevent any eCRM failure before and after implementation which is an essential concern for any organisation in order to gain competitive advantages. In addition to practical implications, the present study contributed to existing literature. This study contributed to the current understanding of eCRM readiness and maturity in banks and helps decision makers to assess their eCRM. This study explores the social and technical aspects of eCRM in the Iranian banking industry. Hence, a pragmatic research approach using mixed methods with a range of stakeholders, such as employees, and managers, was employed in this research. As the purpose of this research is to identify the main eCRM readiness dimensions in Iranian banks and to assess eCRM readiness and maturity, an eCRM readiness/maturity framework was developed. The proposed framework was tested by devising and distributing a structured questionnaire and conducting a semi-structured interview in an attempt to survey a large number of bank employees, and decision makers at five different and well-known private and state banks in Tehran, the capital city of Iran. This survey provides an excellent penetrating study of the Iranian banking industry. Regarding eCRM readiness, data collected from a quantitative approach was analysed statistically using the Software Package for the Social Sciences (SPSS). The qualitative data was interpreted using NVivo, which is a qualitative data analysis computer software package. Findings from the triangulation of data of qualitative and quantitative approaches were evaluated in order to determine the main eCRM readiness dimensions in Iranian banks. Furthermore, from these findings, a case study bank was assessed in regarding eCRM readiness using Analytical Hierarchy Process (AHP). Regarding assessing eCRM maturity, an eCRM maturity model was developed, and a case study bank was selected. Based on the proposed eCRM maturity model, the maturity level of the selected bank was assessed using RADAR logic approach. In addition, this model was based on critical success factors (CSFs) and adapting the CRM3 maturity model. The findings of the empirical research were evaluated against the initial framework, which was generated by integrating the proposed models for eCRM readiness and maturity. This framework consists of three dimensions for eCRM readiness (Organisational culture, corporate strategy, technology) and five level of maturity. Dimensions, factors, and levels in this framework were derived from a literature review. Finally, a revised framework was generated and based on stakeholder’s perceptions, a conclusion was derived, and a recommendation to Iranian banks was made. An eCRM readiness/maturity assessment tool was created to help banks to determine whether they are ready or mature enough for the use of eCRM. The result from this assessment tool can be easily communicated amongst key members, which would help the Iranian banks to improve and promote their eCRM. In addition, this study attempts to fill the current gap in assessing banks eCRM readiness and maturity

On the utility of occupants’ behavioural diversity information for building performance simulation: An exploratory case study

The present study aims at investigating the potential advantages of integrating inter-occupant diversity information into occupant behaviour models used in building performance simulation. To this end, the authors model the operation of windows by occupants in a monitored open-plan office at aggregate and individual levels. The models use indoor and outdoor temperature as well as the interaction of these variables to estimate the probability of opening and closing windows in the building located in Vienna, Austria. Subsequently, a number of existing and novel metrics serve to compare the predictive performance of the aggregate and individual models. In addition, a calibrated energy model of the office area incorporates the window operation models to evaluate their potential contribution to the reliability of building performance assessments. The results of this exploratory case study suggest that individual window operation models outperform the aggregate model in capturing the peak and variations of window operation across occupants. This resulted in a more reliable thermal comfort assessment in the free-running season. The individual models, however, overestimated peak heating demand, as compared with the benchmark value resulting from the actual window operations in a single year

Monitored data on occupants’ presence and actions in an office building

Within a study, an open plan area and one closed office in a university building with a floor area of around 200 m2 were monitored. The present data set covers a period of one year (from 2013-01-01 to 2013-12-31). The collected data pertains to indoor environmental conditions (temperature, humidity) as well as plug loads and external factors (temperature, humidity, wind speed, and global irradiance) along with occupants’ presence and operation of windows and lights. The monitored data can be used for multiple purposes, including the development and validation of occupancy-related models

Overheating mitigation in buildings: a computational exploration of the potential of phase change materials

Phase change materials (PCMs) can store and release thermal energy. The energy is stored when the material goes through a solid-toliquid phase change, and released in the reverse process. Such materials can contribute to the mitigation of overheating in buildings, if their melting and solidification temperatures are in a suitable range. The present contribution entails a computational examination of this potential as relevant to overheating mitigation in typical residential units in the Central European context of Vienna, Austria. Thereby, multiple variations of PCM application (size, thickness, location, and application thickness) under different contextual settings (fenestration and insulation, boundary conditions in terms of weather) were simulated and comparatively evaluated. Results indicate that certain PCM application configurations can significantly influence indoor thermal condition. For instance, PCM elements with larger surface areas displayed a more pronounced effect as compared to bulkier elements with smaller surface areas. Likewise, ceilingintegrated PCM application was found to be more effective that those involving other room surfaces. The results also highlight the importance of rooms ventilation regime if the PCM application potential toward overheating mitigation is to be effectively harvested

Multi-stage calibration of the simulation model of a school building through short-term monitoring

The increasing attention on the improvement of new and existing buildings' performance is emphasizing the importance of the reliability of the simulation models in predicting the complexity of the building behaviour and, consequently, in some advanced applications of building simulation, such as the optimization of the choice of different Energy Efficiency Measures (EEMs) or the adoption of model predictive control strategies. The reliability of the energy model does not depend only on the quality and details of the model itself, but also on the uncertainty related to many input values, such as the physical properties of materials and components, the information on the building management and occupation, and the boundary conditions considered for the simulation. Especially for the existing buildings, this kind of data is often missing or characterized by high uncertainty, and only very simplified behavioural models of occupancy are available. This could compromise the optimization process and undermine the potential of building simulation. In this context, the calibration of the simulation model by means of on-site monitoring is of crucial importance to increase the reliability of the predictions, and to take better decisions, even though this process can be time consuming. This work presents a multi-stage methodology to calibrate the building energy simulation by means of low-cost monitoring and short-term measurements. This approach is applied to a Primary School in the North-East of Italy, which has been monitored from December 2012 to April 2014. Four monitoring periods have been selected to calibrate different sets of variables at a time, while the validation has been carried out on two different periods. The results show that even if less than 8 weeks have been considered in the proposed calibration approach, the maximum error in the estimation of the temperature is less than ±0.5 in 77.3% of the timesteps in the validation period

Combining mammaglobin and carcinoembryonic mRNA markers for early detection of micrometastases from breast cancers - a molecular study of 59 patients

Introduction: As many as 30% of node-negative breast cancer patients relapse within five years, suggesting that current histological detection methods are inadequate for identifying metastatic disease. Detecting small number of cancer cells in the breast tissue or lymph node by reverse transcription-polymerase chain reaction (RT-PCR) assays using a combination of tissue and cancer specific markers might be very useful in the early detection or monitoring of the treatment. Mammaglobin is a member of the uteroglobin gene family and appears to be expressed only in breast tissue. Carcinoembryonic antigen has been the preferred molecular marker for detection of micro metastases in lymph nodes in almost all carcinomas. Materials and Methods: Samples were collected from randomly chosen breast cancer patients undergoing modified mastectomy or breast conserving surgery between September 2003 and July 2004. RT-PCR was applied to study the expression of MMG and CEA markers. Breast cancer micrometastases in axillary lymph nodes were also assessed. Results: The MMG marker was positive in 9/10 normal breast tissues, 3/ 3 breast fibroadenomas and 37/39 of breast carcinoma tissues, giving an overall sensitivity of 94%. The sensitivity was 80% for metastatic lymph node samples. On the other hand CEA showed 95% sensitivity for malignant breast tumors and 100% sensitivity for metastatic lymph nodes. Conclusions: RT-PCR using a combination of MMG and CEA markers is a powerful tool to complement current routine histopathology techniques for detection of breast cancer metastasis in axillary nodes

Edge-guided image gap interpolation using multi-scale transformation

This paper presents improvements in image gap restoration through the incorporation of edge-based directional interpolation within multi-scale pyramid transforms. Two types of image edges are reconstructed: 1) the local edges or textures, inferred from the gradients of the neighboring pixels and 2) the global edges between image objects or segments, inferred using a Canny detector. Through a process of pyramid transformation and downsampling, the image is progressively transformed into a series of reduced size layers until at the pyramid apex the gap size is one sample. At each layer, an edge skeleton image is extracted for edge-guided interpolation. The process is then reversed; from the apex, at each layer, the missing samples are estimated (an iterative method is used in the last stage of upsampling), up-sampled, and combined with the available samples of the next layer. Discrete cosine transform and a family of discrete wavelet transforms are utilized as alternatives for pyramid construction. Evaluations over a range of images, in regular and random loss pattern, at loss rates of up to 40%, demonstrate that the proposed method improves peak-signal-to-noise-ratio by 1–5 dB compared with a range of best-published works

An inquiry into the reliability of window operation models in building performance simulation

Given the impact of inhabitants’ control actions on indoor environment and the complex nature of such interactions, sophisticated models of occupants’ presence and behavior are increasingly deployed to enhance the reliability of building performance simulations. However, the use of occupant behavior models in building simulation efforts and their predictive performance in different contexts involves potentially detrimental uncertainties. To address this issue, the present study deploys long-term monitored data from an office area and its calibrated simulation model to conduct an external evaluation of a number of stochastic and non-stochastic window operation models in view of their a) potential in predicting occupants’ operation of windows, and b) effectiveness to enhance the reliability of building performance simulation efforts. The results suggest that, while stochastic models can emulate the seemingly random character of occupant behavior and provide probabilistic distributions of performance indicators, their use does not guarantee more reliable predictions. Leaving aside the large errors resulted from using such models without the necessary adjustments, stochastic window operation models overestimated the occupants’ operation of windows in heating season and thus the annual and peak heating demands. However, as compared with rule-based models, the stochastic models displayed a better performance in predicting window operations and thermal comfort assessment in the free-running season

On the quality evaluation of behavioural models for building performance applications

Building performance assessment applications require multiple categories of input information. These include, aside from building construction and systems and external conditions, representations of inhabitants. It has been suggested that the representation of people as passive and static entities is unlikely to yield reliable building performance assessment and building operation planning. Rather, adequate representations of building inhabitants should account for dynamics of inhabitants’ presence in buildings and their control-oriented actions (e.g. interactions with buildings indoor environmental control devices and systems). To address these requirements, many recent model development efforts have explored the potential of advanced mathematical formalisms. However, the resulting occupancy-related behavioural models have rarely gone through a rigorous evaluation process. The present contribution is indeed motivated primarily by the lack of explicit procedures and guidelines for the evaluation of proposed user-related behavioural models. Specifically, we formulate a number of conditions that are necessary for systematic and dependable quality assessment of buildings’ inhabitants. Towards this end, we discuss both general model evaluation requirements and specific circumstances pertaining to behavioural models of building inhabitants. By using specific instances of such models, we intend to identify the requirements of a rigorous quality assurance process with regard to behavioural models in building performance assessment applications