Technical entrepreneurship in the UK:an examination of the relationship between the previous occupational background of the technical entrepreneur and the management of the small technology-based venture

With the growing appreciation of the contribution of small technology-based ventures to a healthy economy, an analysis of the individual who initiates and manages such ventures - the technical entrepreneur - is highly desirable, predominantly because of the influence of such an individual on the management and future strategy of the venture. An examination of recent research has indicated that a study of the previous experience and expertise of the entrepreneur, gained in previous occupations, may be highly relevant in determining the possible success of a new venture. This is particularly true where the specific expertise of the entrepreneur forms the main strategic advantage of the business, as in the case of small technology-based firms. Despite this, there has been very little research which has attempted to examine the relationship between the previous occupational background of the technical entrepreneur, and the management of the small technology-based firm. This thesis will examine this relationship, as well as providing an original contribution to the study of technical entrepreneurship in the UK. Consequently, the exploratory nature of the research prompted an inductive qualitative approach being adopted for the thesis. Through a two stage, multiple-site research approach, an examination was made of technical entrepreneurs heading award-winning technology-based small firms in the UK. The main research questions focused on management within the firm, the novelty and origin of the technology adopted, and the personal characteristics of the entrepreneur under study. The results of this study led to the creation of a specific typology for technical entrepreneurs, based on the individual's role in the development of technology within his previous occupation.

Innovation in the pharmaceutical industry:a study of the effects of regulation on the U.K. pharmaceutical industry

A history of government drug regulation and the relationship between the pharmaceutical companies in the U.K. and the licensing authority is outlined. Phases of regulatory stringency are identified with the formation of the Committees on Safety of Drugs and Medicines viewed as watersheds. A study of the impact of government regulation on industrial R&D activities focuses on the effects on the rate and direction of new product innovation. A literature review examines the decline in new chemical entity innovation. Regulations are cited as a major but not singular cause of the decline. Previous research attempting to determine the causes of such a decline on an empirical basis is given and the methodological problems associated with such research are identified. The U.K. owned sector of the British pharmaceutical industry is selected for a study employing a bottom-up approach allowing disaggregation of data. A historical background to the industry is provided, with each company analysed or a case study basis. Variations between companies regarding the policies adopted for R&D are emphasised. The process of drug innovation is described in order to determine possible indicators of the rate and direction of inventive and innovative activity. All possible indicators are considered and their suitability assessed. R&D expenditure data for the period 1960-1983 is subsequently presented as an input indicator. Intermediate output indicators are treated in a similar way and patent data are identified as a readily-available and useful source. The advantages and disadvantages of using such data are considered. Using interview material, patenting policies for most of the U.K. companies are described providing a background for a patent-based study. Sources of patent data are examined with an emphasis on computerised systems. A number of searches using a variety of sources are presented. Patent family size is examined as a possible indicator of an invention's relative importance. The patenting activity of the companies over the period 1960-1983 is given and the variation between companies is noted. The relationship between patent data and other indicators used is analysed using statistical methods resulting in an apparent lack of correlation. An alternative approach taking into account variations in company policy and phases in research activity indicates a stronger relationship between patenting activity, R&D Expenditure and NCE output over the period. The relationship is not apparent at an aggregated company level. Some evidence is presented for a relationship between phases of regulatory stringency, inventive and innovative activity but the importance of other factors is emphasised.

Product innovation in a medium size mature manufacturing company

This thesis is concerned with the management of product innovation inside the medium size, mature, manufacturing company. An academic perspective of innovation is integrated with an account of direct participation acquired over a two year period. The emergent synthesis provides fresh insight into some of the problems associated with producing and sustaining innovation. Product innovation is a very complex activity, and it presents particular difficulties for mature industry. However, the ability to innovate is fundamental to a company's continued survival. Three aspects of product innovation are examined in detail. Firstly, is the requirement to separate innovation activity from the on-going business interests; dependency between the degree of separation and novelty is supported. Secondly, a simple sequential model of the innovation process is tested and shown to be of considerable practical value. Thirdly a relationship is established between the age of the recipient market and the type of innovation to be found in that market All three aspects are found to have important implications for management in their pursuit of innovation. Management deficiencies which inhibited the successful resolution of innovation-linked problems are described and solutions which stress the need for commitment and coherency are proposed. The long existing management structure in the mature company which mitigates against successful and continuing innovation are examined in detail and a strategy is evolved which uses the intrinsic strengths of the mature company to promote innovation of a kind compatible with success in the market. A set of guidelines of practical value is presented for those managers wishing to pursue, and sustain, product innovation in the medium size mature company.

Developing and evaluating a methodology for business process improvement

Purpose – There appears to be an ever-insatiable demand from markets for organisations to improve their products and services. To meet this, there is a need to provide business process improvement (BPI) methodologies that are holistic, structured and procedural. Therefore, this paper describes research that has formed and tested a generic and practical methodology termed model-based and integrated process improvement (MIPI) to support the implementation of BPI; and to validate its effectiveness in organisations. This methodology has been created as an aid for practitioners within organisations. Design/methodology/approach – The research objectives were achieved by: reviewing and analysing current methodologies, and selecting a few frameworks against key performance indicators. Using a refined Delphi approach and semi-structured interview with the “experts” in the field. Intervention, case study and process research approach to evaluating a methodology. Findings – The BPI methodology was successfully formed and applied by the researcher and directly by the companies involved against the criteria of feasibility, usability and usefulness. Research limitations/implications – The paper has demonstrated a new knowledge on how to systematically assess a BPI methodology in practice. Practical implications – Model-based and integrated process improvement methodology (MIPI) methodology offers the practitioner (experienced and novice) a set of step-by-step aids necessary to make informed, consistent and efficient changes to business processes. Originality/value – The novelty of this research work is the creation of a holistic workbook-based methodology with relevant tools and techniques. It extends the capabilities of existing methodologies.

Disentangle contextual and permanent individual motivations:an application to shopping behavior

Past studies resulted in conflicting definitions of consumer motivation. On the one hand, motivations are seen as the consumer’s characteristics that shape her general behavior (motivational trait). On the other hand, they are seen as contextual variables representing the reason why the individual is behaving specific to today’s context (motivational state). The objective of this research is to stress the difference between these two concepts and to understand the impact of each on consumer behavior. We applied our empirical study to shopping motivations; our results show a strong interaction between motivational trait and motivational state. Problem and Hypothesis On the one hand, Westbrook and Black (1985) consider shopping motivations as individual permanent characteristics. This concept is shared by other researchers (Rohm and Swaminathan 2004), which show that some shoppers are functional (they shop for convenience, information seeking, and time saving) while some others are hedonic (they shop for social interaction, bargain hunting and browsing). On the other hand, Kaltcheva and Weitz (2006) define motivations as a contextual orientation changing over time, depending on the situation, and show that contextual shopping motivations have a strong impact on shopping behavior. From our knowledge, no research specifically examined the respective impact of both these shopping motivation types. To deal with this issue, we used the notions of “traits” and “states” that have been largely used in marketing research to designate respectively a permanent characteristic of the individual and a temporary orientation of the consumer (Mowen 2000). The reversal theory (Apter 2001) suggests that two opposite states exist: the telic and the paratelic states. In the telic state, individuals set goals for themselves, must be disciplined to reach these goals, and do not behave in accordance with their personal trait. In the paratelic state, individuals are seeking arousal and enjoyment, do not set rules, and one could postulate that they act in accordance with their natural tendencies. Based on these considerations, we hypothesize the following process: in situations involving paratelic states, hedonic as well as functional individuals should behave according to their natural traits, whereas in situations involving telic states, hedonic people should inhibit their natural propensity to enjoy shopping and behave similarly to functional people. Hence, we postulate the following: Hypothesis: Compared to shoppers with functional motivational trait, shoppers with hedonic motivational trait will a) significantly display more hedonic shopping behavior intentions in a condition of paratelic motivational state, and b) not display more hedonic shopping behavior intentions in a condition a telic motivational state Empirical Research First, 108 participants were asked to fill a multi-items scale about their shopping habits, which actually measured their shopping motivational traits. This questionnaire allowed us to highlight four different dimensions in shopping motivational traits: social interaction, novelty/utility seeking, bargain hunting, and browsing. According to their scores on different items, participants were classified as functional or as hedonic on each of these four dimensions (a single individual may be hedonic on some dimensions and functional on others). Then, participants were then induced to adopt either a telic or a paratelic shopping motivational state while reading an appropriate scenario. Finally, participants were asked for their shopping behavior intentions in response to the shopping context. Four items were developed, corresponding to the four shopping motivational trait dimensions we found with our factor analysis. Results As we found four dimensions in shopping motivational trait, we set up four quasi-experimental designs to capture the entire phenomenon: for each dimension, a 2 (motivational trait) x 2 (motivational state) design was built, where the dependant variable was the shopping behavior element corresponding to the studied dimension. Four 2 x 2 Anovas were performed to assess the interaction between motivational trait and motivational state. Concerning the three dimensions - browsing, novelty/utility seeking, and bargain hunting- , in the paratelic state scenario participants with hedonic motivational trait displayed significantly more hedonic shopping behavior intentions than participants with a functional motivational trait (resp. F = 9.701, p = .003; F = 4.979, p = .03; F = 5.757, p = .02); and in the telic state scenario, there was no significant difference in behavior intentions between participants with hedonic or functional motivation trait. Each time, the interaction effect between motivational state and motivational trait was significant (resp. F = 4.859, p = .03; F = 3.314, p = .07; F = 2.98, p = .08). Concerning the fourth dimension, social interaction, shopping behavior intentions of participants with hedonic and with functional motivational traits were significantly different in the paratelic state scenario (F = 29.898, p <.000) as well as in the telic state scenario (F = 9.559, p = .003). However, the interaction effect showed that this behavioral difference was significantly stronger in the paratelic scenario. All these results support our research hypothesis. Discussion and Implications Our study provides consistent support for our hypotheses saying that there is an interaction effect between shopping motivational states and shopping motivational traits. The generalization of the results is strengthened by the study of four different shopping traits: social interaction, novelty/utility seeking, bargain hunting and browsing. As we proposed, when shopping in a goal-oriented state (telic state), behaviors of hedonic and functional shoppers do not differ significantly. Conversely, when shopping for a recreational reason (paratelic state), hedonic and functional shoppers behave significantly different. These results could explain why some previous studies concluded that shopping motivational traits had no impact on shopping behavior: they did not take into consideration the interaction between motivational trait and motivational state. Moreover, our study shows that marketing surveys performed by store managers to draw the personal profile of their customers must be crossed with contextual motivations in order to accurately forecast shopper behavior. Future Developments Our results can be explained by the self-control process, which pushes hedonic-trait shoppers to behave in a rather functional way in utilitarian situations. However, to be certain that this is the very process that occurs, we plan to add self-control perception scales to our existing measures. This is obviously the next step of this research.

Computationsl modelling of dimethyl ether separation and steam reforming in fluidized bed reactors

This study presents a computational fluid dynamic (CFD) study of Dimethyl Ether (DME) gas adsorptive separation and steam reforming (DME-SR) in a large scale Circulating Fluidized Bed (CFB) reactor. The CFD model is based on Eulerian-Eulerian dispersed flow and solved using commercial software (ANSYS FLUENT). Hydrogen is currently receiving increasing interest as an alternative source of clean energy and has high potential applications, including the transportation sector and power generation. Computational fluid dynamic (CFD) modelling has attracted considerable recognition in the engineering sector consequently leading to using it as a tool for process design and optimisation in many industrial processes. In most cases, these processes are difficult or expensive to conduct in lab scale experiments. The CFD provides a cost effective methodology to gain detailed information up to the microscopic level. The main objectives in this project are to: (i) develop a predictive model using ANSYS FLUENT (CFD) commercial code to simulate the flow hydrodynamics, mass transfer, reactions and heat transfer in a large scale dual fluidized bed system for combined gas separation and steam reforming processes (ii) implement a suitable adsorption models in the CFD code, through a user defined function, to predict selective separation of a gas from a mixture (iii) develop a model for dimethyl ether steam reforming (DME-SR) to predict hydrogen production (iv) carry out detailed parametric analysis in order to establish ideal operating conditions for future industrial application. The project has originated from a real industrial case problem in collaboration with the industrial partner Dow Corning (UK) and jointly funded by the Engineering and Physical Research Council (UK) and Dow Corning. The research examined gas separation by adsorption in a bubbling bed, as part of a dual fluidized bed system. The adsorption process was simulated based on the kinetics derived from the experimental data produced as part of a separate PhD project completed under the same fund. The kinetic model was incorporated in FLUENT CFD tool as a pseudo-first order rate equation; some of the parameters for the pseudo-first order kinetics were obtained using MATLAB. The modelling of the DME adsorption in the designed bubbling bed was performed for the first time in this project and highlights the novelty in the investigations. The simulation results were analysed to provide understanding of the flow hydrodynamic, reactor design and optimum operating condition for efficient separation. Bubbling bed validation by estimation of bed expansion and the solid and gas distribution from simulation agreed well with trends seen in the literatures. Parametric analysis on the adsorption process demonstrated that increasing fluidizing velocity reduced adsorption of DME. This is as a result of reduction in the gas residence time which appears to have much effect compared to the solid residence time. The removal efficiency of DME from the bed was found to be more than 88%. Simulation of the DME-SR in FLUENT CFD was conducted using selected kinetics from literature and implemented in the model using an in-house developed user defined function. The validation of the kinetics was achieved by simulating a case to replicate an experimental study of a laboratory scale bubbling bed by Vicente et al [1]. Good agreement was achieved for the validation of the models, which was then applied in the DME-SR in the large scale riser section of the dual fluidized bed system. This is the first study to use the selected DME-SR kinetics in a circulating fluidized bed (CFB) system and for the geometry size proposed for the project. As a result, the simulation produced the first detailed data on the spatial variation and final gas product in such an industrial scale fluidized bed system. The simulation results provided insight in the flow hydrodynamic, reactor design and optimum operating condition. The solid and gas distribution in the CFB was observed to show good agreement with literatures. The parametric analysis showed that the increase in temperature and steam to DME molar ratio increased the production of hydrogen due to the increased DME conversions, whereas the increase in the space velocity has been found to have an adverse effect. Increasing temperature between 200 oC to 350 oC increased DME conversion from 47% to 99% while hydrogen yield increased substantially from 11% to 100%. The CO2 selectivity decreased from 100% to 91% due to the water gas shift reaction favouring CO at higher temperatures. The higher conversions observed as the temperature increased was reflected on the quantity of unreacted DME and methanol concentrations in the product gas, where both decreased to very low values of 0.27 mol% and 0.46 mol% respectively at 350 °C. Increasing the steam to DME molar ratio from 4 to 7.68 increased the DME conversion from 69% to 87%, while the hydrogen yield increased from 40% to 59%. The CO2 selectivity decreased from 100% to 97%. The decrease in the space velocity from 37104 ml/g/h to 15394 ml/g/h increased the DME conversion from 87% to 100% while increasing the hydrogen yield from 59% to 87%. The parametric analysis suggests an operating condition for maximum hydrogen yield is in the region of 300 oC temperatures and Steam/DME molar ratio of 5. The analysis of the industrial sponsor’s case for the given flow and composition of the gas to be treated suggests that 88% of DME can be adsorbed from the bubbling and consequently producing 224.4t/y of hydrogen in the riser section of the dual fluidized bed system. The process also produces 1458.4t/y of CO2 and 127.9t/y of CO as part of the product gas. The developed models and parametric analysis carried out in this study provided essential guideline for future design of DME-SR at industrial level and in particular this work has been of tremendous importance for the industrial collaborator in order to draw conclusions and plan for future potential implementation of the process at an industrial scale.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

The multiple pheromone ant clustering algorithm and its application to real world domains

The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models. © 2013 Polish Information Processing Society.

The value of innovation:the interaction of competition, R&D and IP

This paper analyses market valuations of UK companies using a new data set of their R&D and IP activities (1989–2002). In contrast to previous studies, the analysis is conducted at the sectoral-level, where the sectors are based on the technological classification originating from Pavitt [Pavitt, K., 1984. Sectoral patterns of technical change. Research Policy 13, 343–373]. The first main result is that the valuation of R&D varies substantially across these sectors. Another important result is that, on average, firms that receive only UK patents tend to have no significant market premium. In direct contrast, patenting through the European Patent Office does raise market value, as does the registration of trade marks in the UK for most sectors. To explore these variations the paper links competitive conditions with the market valuation of innovation. Using profit persistence as a measure of competitive pressure, we find that the sectors that are the most competitive have the lowest market valuation of R&D. Furthermore, within the most competitive sector (‘science based’ manufacturing), firms with larger market shares (an inverse indicator of competitive pressure) also have higher R&D valuations, as well as some positive return to UK patents. We conclude that this evidence supports Schumpeter by finding higher returns to innovation in less than fully competitive markets and contradicts Arrow [Arrow, K., 1962. Economic welfare and the allocation of resources for invention. In: Nelson, R. (Ed.), The Rate and Direction of Inventive Activity. Princeton University Press, Princeton], who argued that, with the existence of IP rights, competitive market structure provides higher incentives to innovate.

Singapore's online retail deviants:analyzing the rise of blogshops' power

Geography, retailing, and power are institutionally bound up together. Within these, the authors situate their research in Clegg's work on power. Online shopping offers a growing challenge to the apparent hegemony of traditional physical retail stores' format. While novel e-formats appear regularly, blogshops in Singapore are enjoying astonishing success that has taken the large retailers by surprise. Even though there are well-developed theoretical frameworks for understanding the role of institutional entrepreneurs and other major stakeholders in bringing about change and innovation, much less attention has been paid to the role of unorganized, nonstrategic actors-such as blogshops-in catalyzing retail change. The authors explore how blogshops are perceived by consumers and how they challenge the power of other shopping formats. They use Principal Components Analysis to analyze results from a survey of 349 blogshops users. While the results show that blogshops stay true to traditional online shopping attributes, deviations occur on the concept of value. Furthermore, consumer power is counter intuitively found to be strongly present in the areas related to cultural ties, excitement, and search for individualist novelty (as opposed to mass-production), thereby encouraging researchers to think critically about emerging power behavior in media practices.

Simulation process of biodiesel production over heterogeneous catalysts

Biodiesel production is a very promising area due to the relevance that it is an environmental-friendly diesel fuel alternative to fossil fuel derived diesel fuels. Nowadays, most industrial applications of biodiesel production are performed by the transesterification of renewable biological sources based on homogeneous acid catalysts, which requires downstream neutralization and separation leading to a series of technical and environmental problems. However, heterogeneous catalyst can solve these issues, and be used as a better alternative for biodiesel production. Thus, a heuristic diffusion-reaction kinetic model has been established to simulate the transesterification of alkyl ester with methanol over a series of heterogeneous Cs-doped heteropolyacid catalysts. The novelty of this framework lies in detailed modeling of surface reacting kinetic phenomena and integrating that with particle-level transport phenomena all the way through to process design and optimisation, which has been done for biodiesel production process for the first time. This multi-disciplinary research combining chemistry, chemical engineering and process integration offers better insights into catalyst design and process intensification for the industrial application of Cs-doped heteropolyacid catalysts for biodiesel production. A case study of the transesterification of tributyrin with methanol has been demonstrated to establish the effectiveness of this methodology.

Simulation process of biodiesel production over heterogeneous catalysts

Biodiesel production is a very promising area due to the relevance that it is an environmental-friendly diesel fuel alternative to fossil fuel derived diesel fuels. Nowadays, most industrial applications of biodiesel production are performed by the transesterification of renewable biological sources based on homogeneous acid catalysts, which requires downstream neutralization and separation leading to a series of technical and environmental problems. However, heterogeneous catalyst can solve these issues, and be used as a better alternative for biodiesel production. Thus, a heuristic diffusion-reaction kinetic model has been established to simulate the transesterification of alkyl ester with methanol over a series of heterogeneous Cs-doped heteropolyacid catalysts. The novelty of this framework lies in detailed modeling of surface reacting kinetic phenomena and integrating that with particle-level transport phenomena all the way through to process design and optimisation, which has been done for biodiesel production process for the first time. This multi-disciplinary research combining chemistry, chemical engineering and process integration offers better insights into catalyst design and process intensification for the industrial application of Cs-doped heteropolyacid catalysts for biodiesel production. A case study of the transesterification of tributyrin with methanol has been demonstrated to establish the effectiveness of this methodology.

Consumer trial, continuous use, and economic benefits of a retail service innovation:the case of the personal shopping assistant

Service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific self-service technology (SST), the personal shopping assistant (PSA), and estimates retailer benefits from implementing that innovation. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the technology acceptance model (TAM), this study develops specific hypotheses and tests them on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device. Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in-store service innovations. Incorporation of technology within physical stores affords opportunities for the retailer to reduce costs, while enhancing service provided to consumers. Therefore, service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific SST in the retail context, the PSA, and estimates retailer benefits from implementing that innovation. In so doing, the study contributes to the nascent area of research on SSTs in the retail sector. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the TAM, this study develops specific hypotheses regarding the (1) antecedent effects of technological anxiety, novelty seeking, market mavenism, and trust in the retailer on trial of the service innovation; (2) the effects of ease of use, perceived waiting time, and need for interaction on continuous use of the innovation; and (3) the effect of use of innovation on consumer spending at the store. The hypotheses were tested on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device, one of the early adopters of PSA in Germany. Data were analyzed using logistic regression (antecedents of trial), multiple regression (antecedents of continuous use), and propensity score matching (assessing retailer benefits). Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use, while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in-store service innovations. The study contributes to the literature through its (1) simultaneous examination of antecedents of trial and continuous usage of a specific SST, (2) the demonstration of economic benefits of SST introduction for the retailer, and (3) contribution to the stream of research on service innovation, as against product innovation.

Corporate governance and compliance with International Financial Reporting Standards (IFRSs):evidence from two MENA stock exchanges

This study examines the influence of corporate governance structures on the levels of compliance with IFRSs disclosure requirements by companies listed on the stock exchanges of two leading MENA (Middle East and North Africa) countries, Egypt and Jordan. This study employs a cross-sectional analysis of a sample of non-financial companies listed on the two stock exchanges for the fiscal year 2007. Using an unweighted disclosure index, the study measures the levels of compliance by companies listed on the two stock exchanges investigated.Univariate and multivariate regression analyses are used to estimate the relationships proposed in the hypotheses. In addition, the study uses semi-structured interviews in order to supplement the interpretation of the findings of the quantitative analyses. An innovative theoretical foundation is deployed, in which compliance is interpretable through three lenses - institutional isomorphism theory, secrecy versus transparency (one of Gray’s accounting sub-cultural values), and financial economics theories. The study extends the financial reporting literature, cross-national comparative financial disclosure literature, and the emerging markets disclosure literature by carrying out one of the first comparative studies of the above mentioned stock exchanges. Results provide evidence of a lack of de facto compliance (i.e., actual compliance) with IFRSs disclosure requirements in the scrutinised MENA countries. The impact of corporate governance mechanisms for best practice on enhancing the extent of compliance with mandatory IFRSs is absent in the stock exchanges in question. The limited impact of corporate governance best practice is mainly attributed to the novelty of corporate governance in the region, a finding which lends support to the applicability of the proposed theoretical foundation to the MENA context. Finally, the study provides recommendations for improving de facto compliance with IFRSs disclosure requirements and corporate governance best practice in the MENA region and suggests areas for future research.

Editorial overview:new protein production tools for structural biology

Full text: The idea of producing proteins from recombinant DNA hatched almost half a century ago. In his PhD thesis, Peter Lobban foresaw the prospect of inserting foreign DNA (from any source, including mammalian cells) into the genome of a λ phage in order to detect and recover protein products from Escherichia coli [ 1 and 2]. Only a few years later, in 1977, Herbert Boyer and his colleagues succeeded in the first ever expression of a peptide-coding gene in E. coli — they produced recombinant somatostatin [ 3] followed shortly after by human insulin. The field has advanced enormously since those early days and today recombinant proteins have become indispensable in advancing research and development in all fields of the life sciences. Structural biology, in particular, has benefitted tremendously from recombinant protein biotechnology, and an overwhelming proportion of the entries in the Protein Data Bank (PDB) are based on heterologously expressed proteins. Nonetheless, synthesizing, purifying and stabilizing recombinant proteins can still be thoroughly challenging. For example, the soluble proteome is organized to a large part into multicomponent complexes (in humans often comprising ten or more subunits), posing critical challenges for recombinant production. A third of all proteins in cells are located in the membrane, and pose special challenges that require a more bespoke approach. Recent advances may now mean that even these most recalcitrant of proteins could become tenable structural biology targets on a more routine basis. In this special issue, we examine progress in key areas that suggests this is indeed the case. Our first contribution examines the importance of understanding quality control in the host cell during recombinant protein production, and pays particular attention to the synthesis of recombinant membrane proteins. A major challenge faced by any host cell factory is the balance it must strike between its own requirements for growth and the fact that its cellular machinery has essentially been hijacked by an expression construct. In this context, Bill and von der Haar examine emerging insights into the role of the dependent pathways of translation and protein folding in defining high-yielding recombinant membrane protein production experiments for the common prokaryotic and eukaryotic expression hosts. Rather than acting as isolated entities, many membrane proteins form complexes to carry out their functions. To understand their biological mechanisms, it is essential to study the molecular structure of the intact membrane protein assemblies. Recombinant production of membrane protein complexes is still a formidable, at times insurmountable, challenge. In these cases, extraction from natural sources is the only option to prepare samples for structural and functional studies. Zorman and co-workers, in our second contribution, provide an overview of recent advances in the production of multi-subunit membrane protein complexes and highlight recent achievements in membrane protein structural research brought about by state-of-the-art near-atomic resolution cryo-electron microscopy techniques. E. coli has been the dominant host cell for recombinant protein production. Nonetheless, eukaryotic expression systems, including yeasts, insect cells and mammalian cells, are increasingly gaining prominence in the field. The yeast species Pichia pastoris, is a well-established recombinant expression system for a number of applications, including the production of a range of different membrane proteins. Byrne reviews high-resolution structures that have been determined using this methylotroph as an expression host. Although it is not yet clear why P. pastoris is suited to producing such a wide range of membrane proteins, its ease of use and the availability of diverse tools that can be readily implemented in standard bioscience laboratories mean that it is likely to become an increasingly popular option in structural biology pipelines. The contribution by Columbus concludes the membrane protein section of this volume. In her overview of post-expression strategies, Columbus surveys the four most common biochemical approaches for the structural investigation of membrane proteins. Limited proteolysis has successfully aided structure determination of membrane proteins in many cases. Deglycosylation of membrane proteins following production and purification analysis has also facilitated membrane protein structure analysis. Moreover, chemical modifications, such as lysine methylation and cysteine alkylation, have proven their worth to facilitate crystallization of membrane proteins, as well as NMR investigations of membrane protein conformational sampling. Together these approaches have greatly facilitated the structure determination of more than 40 membrane proteins to date. It may be an advantage to produce a target protein in mammalian cells, especially if authentic post-translational modifications such as glycosylation are required for proper activity. Chinese Hamster Ovary (CHO) cells and Human Embryonic Kidney (HEK) 293 cell lines have emerged as excellent hosts for heterologous production. The generation of stable cell-lines is often an aspiration for synthesizing proteins expressed in mammalian cells, in particular if high volumetric yields are to be achieved. In his report, Buessow surveys recent structures of proteins produced using stable mammalian cells and summarizes both well-established and novel approaches to facilitate stable cell-line generation for structural biology applications. The ambition of many biologists is to observe a protein's structure in the native environment of the cell itself. Until recently, this seemed to be more of a dream than a reality. Advances in nuclear magnetic resonance (NMR) spectroscopy techniques, however, have now made possible the observation of mechanistic events at the molecular level of protein structure. Smith and colleagues, in an exciting contribution, review emerging ‘in-cell NMR’ techniques that demonstrate the potential to monitor biological activities by NMR in real time in native physiological environments. A current drawback of NMR as a structure determination tool derives from size limitations of the molecule under investigation and the structures of large proteins and their complexes are therefore typically intractable by NMR. A solution to this challenge is the use of selective isotope labeling of the target protein, which results in a marked reduction of the complexity of NMR spectra and allows dynamic processes even in very large proteins and even ribosomes to be investigated. Kerfah and co-workers introduce methyl-specific isotopic labeling as a molecular tool-box, and review its applications to the solution NMR analysis of large proteins. Tyagi and Lemke next examine single-molecule FRET and crosslinking following the co-translational incorporation of non-canonical amino acids (ncAAs); the goal here is to move beyond static snap-shots of proteins and their complexes and to observe them as dynamic entities. The encoding of ncAAs through codon-suppression technology allows biomolecules to be investigated with diverse structural biology methods. In their article, Tyagi and Lemke discuss these approaches and speculate on the design of improved host organisms for ‘integrative structural biology research’. Our volume concludes with two contributions that resolve particular bottlenecks in the protein structure determination pipeline. The contribution by Crepin and co-workers introduces the concept of polyproteins in contemporary structural biology. Polyproteins are widespread in nature. They represent long polypeptide chains in which individual smaller proteins with different biological function are covalently linked together. Highly specific proteases then tailor the polyprotein into its constituent proteins. Many viruses use polyproteins as a means of organizing their proteome. The concept of polyproteins has now been exploited successfully to produce hitherto inaccessible recombinant protein complexes. For instance, by means of a self-processing synthetic polyprotein, the influenza polymerase, a high-value drug target that had remained elusive for decades, has been produced, and its high-resolution structure determined. In the contribution by Desmyter and co-workers, a further, often imposing, bottleneck in high-resolution protein structure determination is addressed: The requirement to form stable three-dimensional crystal lattices that diffract incident X-ray radiation to high resolution. Nanobodies have proven to be uniquely useful as crystallization chaperones, to coax challenging targets into suitable crystal lattices. Desmyter and co-workers review the generation of nanobodies by immunization, and highlight the application of this powerful technology to the crystallography of important protein specimens including G protein-coupled receptors (GPCRs). Recombinant protein production has come a long way since Peter Lobban's hypothesis in the late 1960s, with recombinant proteins now a dominant force in structural biology. The contributions in this volume showcase an impressive array of inventive approaches that are being developed and implemented, ever increasing the scope of recombinant technology to facilitate the determination of elusive protein structures. Powerful new methods from synthetic biology are further accelerating progress. Structure determination is now reaching into the living cell with the ultimate goal of observing functional molecular architectures in action in their native physiological environment. We anticipate that even the most challenging protein assemblies will be tackled by recombinant technology in the near future.