Mohammad T Islam (BSc, MBA, MEd)

Different Types of Organisations: Understanding Business Structures, Purposes and Legal Frameworks

by

✧ The modern economy is shaped by different types of organisations, each designed to meet a particular need, pursue a specific purpose, and operate within a distinct legal framework. Some organisations exist to generate profit and reward investors, while others are formed to deliver social value, support communities, or address humanitarian and environmental challenges. At the same time, organisations vary significantly in size, from micro enterprises serving a local neighbourhood to large companies operating across international markets. Understanding different types of organisations is important because organisational form influences ownership, accountability, taxation, liability, funding, and decision-making. It also affects how success is measured. For a commercial company, success may be defined by profitability and growth. For a charity or NGO, success is more likely to be assessed through social impact and mission fulfilment (Anheier, 2014). Likewise, the legal structure chosen by an organisation determines how much risk owners carry and how easily capital can be raised (Davies, 2010). This article examines different types of organisations by exploring their purposes, structures, and legal frameworks. Particular attention is given to for-profit organisations, not-for-profit organisations, NGOs, SMEs, and the legal forms of sole traders, partnerships, and limited companies. 1.0 For-Profit and Not-for-Profit Organisations 1.1 For-Profit Organisations and Their Purpose Among the different types of organisations, for-profit organisations are the most directly associated with commerce and market activity. Their central purpose is to generate financial returns for owners, shareholders, or investors. These organisations range from small family-run firms to multinational corporations. Profit earned may either be distributed as dividends or reinvested to support expansion, innovation, and competitiveness (Bragg, 2011). For-profit organisations usually focus on objectives such as maximising shareholder value, increasing market share, improving efficiency, and achieving long-term sustainability. They play a major role in the economy by generating employment, encouraging innovation, and contributing to national income. For example, a retail chain may seek to open new stores, increase sales volume, and strengthen its brand presence in order to improve profitability. However, profit-making does not mean that these organisations lack wider social importance. In many economies, businesses are key drivers of product development, consumer choice, and tax revenue, all of which support broader economic progress. 1.2 Not-for-Profit Organisations and Social Value A second major category within different types of organisations is the not-for-profit organisation. These organisations are not established to distribute profits to owners or shareholders. Instead, any financial surplus is reinvested into the organisation’s activities in order to support its mission. Their purpose may involve education, health, religion, culture, social welfare, or community development (Anheier, 2014). Success in a not-for-profit context is measured less by financial gain and more by public benefit and mission impact. A charity supporting homeless people, for instance, would judge effectiveness through outcomes such as the number of individuals housed or supported, rather than through profit margins. Financial sustainability remains necessary, but it is a means to an end rather than the principal goal. This distinction highlights an important feature of different types of organisations: organisations are not only economic units but also social institutions with varied priorities and responsibilities. 1.3 NGOs as a Specialised Form of Not-for-Profit Organisation Non-governmental organisations (NGOs) represent a specific and highly visible form of not-for-profit organisation. NGOs operate independently of direct government control and are commonly involved in human rights, environmental protection, poverty reduction, disaster relief, and advocacy (Werker and Ahmed, 2008). NGOs often rely on a combination of donations, grants, fundraising, and volunteer support. Because they frequently address sensitive or urgent public issues, their legitimacy depends heavily on transparency, accountability, and trust. International NGOs such as humanitarian agencies often work across borders, influencing policy as well as delivering services. In the landscape of different types of organisations, NGOs are especially significant because they bridge the gap between the public, private, and governmental sectors. They may campaign against inequality, provide essential services where state provision is weak, or collaborate with businesses on corporate social responsibility initiatives. 2.0 Micro, Small, and Medium‑Sized Enterprises (SMEs) 2.1 Why SMEs Matter Another way of understanding different types of organisations is through size. Small and medium-sized enterprises (SMEs) are widely recognised as the backbone of many economies because of their contribution to employment, innovation, entrepreneurship, and local development (Beck, Demirguc-Kunt and Levine, 2005). They are typically classified according to employee numbers, although turnover and balance sheet size may also be considered (European Commission, 2003). 2.2 Micro Enterprises Micro enterprises generally employ fewer than 10 people and tend to operate on a very small scale. These businesses are often owner-managed and may include local cafés, market stalls, tradespeople, online craft sellers, or home-based service providers. Their goals commonly centre on self-employment, survival, flexibility, and community service (Berger and Udell, 2006). Because they are small, micro enterprises often benefit from quick decision-making and close customer relationships. At the same time, they may face challenges such as limited access to finance, vulnerability to market shocks, and restricted capacity for expansion. 2.3 Small Enterprises Small enterprises, usually employing 10 to 49 people, are more structured than micro businesses. They may employ specialist staff, adopt more formal procedures, and target niche markets. A small manufacturing firm, for example, may supply a regional customer base while developing a reputation for quality and reliability. Within different types of organisations, small enterprises often occupy an important middle ground: they are still agile, but they also begin to show the characteristics of more established businesses, including clearer management roles and modest growth ambitions. 2.4 Medium-sized Enterprises Medium-sized enterprises typically employ 50 to 249 people and often have more developed management systems and operational processes. They may trade nationally or internationally, diversify their products, and seek investment to support further growth. Such organisations are important because they combine entrepreneurial dynamism with greater organisational capacity. According to the European Commission (2003) and the UK Department for Business, Energy and Industrial Strategy (BEIS, 2021), the broad categories are as follows: Micro: fewer than 10 employees Small: 10–49 employees Medium: 50–249 employees Large: 250 or more employees These classifications show that … Read more

Characteristics of Average and Great Employees

by

In the contemporary workplace, employees can broadly be classified into two categories: average employees and great employees. This distinction is critical for organisational success, as the collective performance of individuals directly influences productivity, innovation, and workplace culture. Recognising and understanding the attributes that separate great employees from their average counterparts enables organisations to design effective talent management strategies, build high-performance teams, and foster an environment where excellence thrives. This article explores the key characteristics of average versus great employees, examining their behaviours, motivations, and contributions. It also highlights how organisations can cultivate a culture that nurtures greatness among employees. 1.0 Average Employees Average employees typically do what is required of them but rarely go beyond expectations. Their attitudes and behaviours often reveal patterns that undermine both individual growth and collective performance. 1.1 Lack of Motivation and Engagement Average employees often come to work primarily for the paycheque, with their motivation being largely extrinsic. They lack the intrinsic drive to excel and may show minimal curiosity or interest in learning new skills. According to Deci and Ryan’s (1985) Self-Determination Theory, intrinsic motivation—engaging in work out of genuine interest and satisfaction—leads to superior outcomes compared to extrinsic motivation. Employees who lack this intrinsic motivation risk stagnating, both personally and professionally. 1.2 Resistance to Change Change is an unavoidable reality in the modern workplace. However, average employees tend to resist change, clinging to the comfort of established routines. This rigidity can stifle innovation and hinder organisational adaptability. Kotter (1996) argues that resistance to change is a major barrier to organisational transformation, often causing delays in implementation and creating inefficiencies. 1.3 Poor Planning and Health Habits Average employees frequently struggle with time management and planning, leading to inefficiencies, missed deadlines, and reduced productivity. Their approach to tasks is often reactive rather than proactive. In addition, poor health habits such as lack of exercise, poor diet, or inadequate sleep may contribute to absenteeism, reduced energy, and lower resilience. Cooper, Dewe and O’Driscoll (2001) highlight how stress and poor health behaviours negatively impact both productivity and overall organisational performance. 1.4 Blame Culture and Fear-Based Motivation When mistakes occur, average employees often resort to blame-shifting rather than taking responsibility. This behaviour fosters a toxic work environment where accountability is lacking. Kane-Urrabazo (2006) emphasises that fear-based motivation, where employees act out of anxiety rather than ambition, erodes trust and stifles collaboration. Such cultures prevent individuals from learning from mistakes and adapting effectively. 1.5 Lack of Contribution and Team Spirit Average employees tend to contribute only the minimum required, showing limited initiative. They rarely offer new ideas or challenge existing processes. Furthermore, their lack of enthusiasm can dampen team morale. Edmondson (1999) introduced the concept of psychological safety, arguing that teams thrive when individuals feel safe to contribute ideas and take risks. Average employees, however, often avoid contributing meaningfully, thereby weakening team dynamics. 2.0 Great Employees Great employees distinguish themselves through their mindset, behaviours, and impact. They bring energy, innovation, and accountability to their roles, elevating not only their own performance but also that of those around them. 2.1 Passion for Work and Continuous Learning Great employees are driven by intrinsic motivation. They take pride in their work and strive for excellence beyond external rewards. They actively pursue continuous learning, acquiring new skills to remain relevant in a rapidly changing environment. According to Kolb’s (1984) Experiential Learning Theory, individuals who embrace learning cycles—through reflection, conceptualisation, and experimentation—are better equipped to adapt and innovate. 2.2 Embracing Change Unlike their average counterparts, great employees view change as an opportunity rather than a threat. Their adaptability enables organisations to transition smoothly during restructuring, technological advancements, or shifts in market demands. Heifetz, Grashow and Linsky (2009) describe adaptability as a hallmark of effective leadership, with employees who embrace change contributing significantly to long-term resilience. 2.3 Strategic Planning and Health Consciousness Great employees demonstrate strong self-management skills, including planning, prioritisation, and goal-setting. They work systematically and set ambitious yet achievable objectives. Moreover, they understand the link between physical well-being and productivity. Maintaining healthy habits enables them to sustain high levels of energy and focus. Cameron and Quinn (2011) emphasise the importance of personal discipline and resilience in fostering a high-performance culture. 2.4 Responsibility and Excellence Accountability is a defining trait of great employees. They readily take ownership of their actions, learning from setbacks rather than deflecting blame. This proactive approach fosters a culture of excellence. Covey (1989) argues that individuals who embrace responsibility are better positioned to achieve lasting success, as they focus on solutions rather than excuses. 2.5 Contribution and Leadership Great employees are often the innovators within teams, consistently contributing fresh ideas and process improvements. They are proactive problem-solvers who dislike inefficiency. Their ability to inspire and motivate peers often positions them as informal leaders, regardless of their job title. Senge (1990) notes that organisations thrive when individuals contribute to the collective learning process, a trait commonly embodied by great employees. Their positive attitude and collaborative spirit enhance team cohesion and workplace culture. 3.0 Cultivating Great Employees While some traits of great employees may be innate, organisations play a crucial role in nurturing and developing greatness. 3.1 Building a Learning Culture Organisations should encourage continuous learning and development. By investing in training programmes, mentorship opportunities, and career development initiatives, employers can transform average performers into great employees. Garavan et al. (2021) highlight that a culture of learning enhances both engagement and performance. 3.2 Promoting Psychological Safety Encouraging employees to share ideas without fear of ridicule fosters innovation and collaboration. Edmondson (1999) emphasises that creating a climate of psychological safety allows employees to take risks, challenge the status quo, and grow. 3.3 Rewarding Initiative and Innovation Recognising and rewarding employees who go beyond basic expectations reinforces desirable behaviours. Recognition programmes that value not only performance outcomes but also creativity, teamwork, and accountability are particularly effective (Armstrong and Taylor, 2020). 3.4 Leadership and Role Modelling Managers and leaders must act as role models, demonstrating the traits of great employees—passion, adaptability, and accountability. Employees … Read more

Computer Networks and the Internet: Foundations and Advancements

by

Computer networks, including the Internet, are indispensable for communication and information exchange in today’s connected world. They enable the seamless transfer of data between computers and other devices, facilitating various applications from personal communication to business transactions. This article explores the design, implementation, and management of networks, highlighting key concepts such as network protocols, architecture, security, and performance. Network Architecture and Protocols Network Architecture The architecture of computer networks encompasses the layout and structure of interconnected devices. The fundamental model is the OSI (Open Systems Interconnection) model, which divides network functions into seven layers: physical, data link, network, transport, session, presentation, and application. This layered approach allows for modular design and troubleshooting. Kurose and Ross (2017) detail the OSI model’s relevance, explaining how each layer serves a specific function in data transmission (Kurose & Ross, 2017). Network Protocols Protocols are essential for ensuring reliable communication over networks. They define rules and conventions for data exchange. The TCP/IP (Transmission Control Protocol/Internet Protocol) suite is the cornerstone of Internet communication, comprising several protocols that manage different aspects of data transmission. HTTP (Hypertext Transfer Protocol), for instance, governs web communication, while SMTP (Simple Mail Transfer Protocol) handles email transmission. The robust framework provided by these protocols is crucial for maintaining the Internet’s functionality (Tanenbaum & Wetherall, 2011). Security in Computer Networks Network Security Challenges With the proliferation of online services, network security has become paramount. Networks are vulnerable to various threats, including malware, phishing attacks, and DDoS (Distributed Denial of Service) attacks. These threats can compromise sensitive information, disrupt services, and cause significant financial losses. Stallings (2016) emphasises the need for robust security measures to protect network infrastructure and data integrity (Stallings, 2016). Security Measures Effective security strategies include encryption, firewalls, intrusion detection systems, and secure network protocols. Encryption ensures that data is readable only by authorised parties, while firewalls block unauthorised access to networks. Intrusion detection systems monitor network traffic for suspicious activities, and secure protocols like HTTPS (Hypertext Transfer Protocol Secure) provide an additional layer of security for online transactions. Implementing these measures helps mitigate risks and enhances the overall security of computer networks (Kurose & Ross, 2017). Performance and Management Network Performance Network performance is a critical aspect that affects the user experience. Key performance indicators include bandwidth, latency, and throughput. Bandwidth refers to the maximum data transfer rate, latency is the delay in data transmission, and throughput is the actual rate of successful data transfer. Optimising these factors is essential for ensuring efficient network operation, particularly in high-demand environments such as data centres and cloud services (Tanenbaum & Wetherall, 2011). Network Management Managing computer networks involves monitoring and maintaining network infrastructure to ensure optimal performance and reliability. Network administrators use various tools and techniques to detect issues, perform routine maintenance, and upgrade systems. Network management protocols like SNMP (Simple Network Management Protocol) facilitate the monitoring and control of network devices. Effective management practices are vital for sustaining the functionality and scalability of networks (Stallings, 2016). The Future of Computer Networks Emerging Technologies The future of computer networks is shaped by emerging technologies such as 5G, IoT (Internet of Things), and AI (Artificial Intelligence). 5G technology promises higher speeds and lower latency, enabling new applications like augmented reality and autonomous vehicles. IoT connects a vast array of devices, creating smart environments and enhancing automation. AI improves network management and security through advanced analytics and automated decision-making (Andrews et al., 2014). Challenges and Opportunities While these advancements offer significant benefits, they also present challenges such as increased complexity and the need for enhanced security measures. Addressing these challenges requires continuous innovation and collaboration among researchers, industry professionals, and policymakers. The ongoing evolution of computer networks will undoubtedly drive further progress and transform various aspects of daily life and business operations (Kurose & Ross, 2017). Computer networks and the Internet are the backbone of modern communication and information exchange. Understanding their architecture, protocols, security, and performance is essential for leveraging their full potential. As technology continues to evolve, addressing the challenges and seizing the opportunities presented by emerging trends will be crucial for the continued growth and advancement of computer networks. References Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C., & Zhang, J. C. (2014) “What will 5G be?”. IEEE Journal on Selected Areas in Communications. 32(6), pp. 1065-1082. Kurose, J. F., & Ross, K. W. (2017) Computer Networking: A Top-Down Approach. 7th ed. Pearson. Stallings, W. (2016) Foundations of Modern Networking: SDN, NFV, QoE, IoT, and Cloud. Addison-Wesley. Tanenbaum, A. S., & Wetherall, D. J. (2011) Computer Networks. 5th ed. Prentice Hall.

Artificial Intelligence and Machine Learning: Transforming Modern Technology

by

Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of modern computer science, catalysing transformative advancements across various sectors including healthcare, finance, and autonomous systems. AI encompasses the development of systems that can perform tasks requiring human intelligence, such as visual perception, speech recognition, and decision-making. ML, a crucial subset of AI, focuses on the development of algorithms that enable computers to learn from data and make predictions. These technologies are not only reshaping industries but also redefining the boundaries of what machines can achieve. Applications of AI and ML Healthcare AI’s scope extends to numerous applications, enhancing the efficiency and effectiveness of processes in different domains. In healthcare, for instance, AI-driven diagnostic tools have demonstrated remarkable accuracy in identifying diseases from medical images, thereby aiding early detection and treatment. Esteva et al. (2017) highlight the impact of deep learning, a branch of ML, in dermatology, where algorithms have achieved dermatologist-level classification of skin cancer from images. This application underscores the potential of AI to complement human expertise, leading to improved healthcare outcomes (Esteva et al., 2017). Finance The financial sector has also witnessed significant transformations due to AI and ML. These technologies are utilised for fraud detection, risk management, and personalised customer services. By analysing vast amounts of transaction data, ML algorithms can identify unusual patterns indicative of fraudulent activities. Furthermore, AI-powered chatbots and virtual assistants provide personalised financial advice and support, enhancing customer experience and operational efficiency (Brown & Hagen, 2018). Autonomous Systems Autonomous systems, such as self-driving cars, are another area where AI and ML have made substantial progress. These systems rely on complex algorithms and sensor data to navigate and make real-time decisions, aiming to enhance safety and efficiency in transportation. Goodfellow, Bengio, and Courville (2016) discuss the advancements in ML techniques that have enabled significant improvements in autonomous driving technologies, emphasising the role of neural networks and reinforcement learning in developing sophisticated control systems (Goodfellow, Bengio, & Courville, 2016). Foundations and Ethical Considerations Theoretical Frameworks The development of AI and ML is grounded in robust theoretical frameworks and practical implementations. Russell and Norvig’s “Artificial Intelligence: A Modern Approach” provides a comprehensive overview of the principles and applications of these technologies. The book delves into various AI techniques, including search algorithms, knowledge representation, and learning methods, offering insights into the foundational aspects of AI and its real-world applications (Russell & Norvig, 2020). Ethical Considerations Ethical considerations are paramount in the deployment of AI and ML technologies. Issues such as data privacy, algorithmic bias, and the potential for job displacement necessitate careful deliberation and regulation. Mittelstadt et al. (2016) emphasise the importance of ethical frameworks to guide the development and implementation of AI, advocating for transparency, accountability, and fairness in AI systems (Mittelstadt et al., 2016). Addressing these ethical concerns is crucial to ensuring that AI technologies benefit society as a whole. Future Directions The future of AI and ML holds immense potential for further innovation and societal impact. Continuous advancements in computational power, data availability, and algorithmic techniques are expected to drive the evolution of AI capabilities. Researchers and practitioners are exploring new frontiers, such as explainable AI, which aims to make AI decision-making processes more transparent and understandable to humans (Gunning, 2017). AI and ML are pivotal in driving technological progress across various domains. Their applications in healthcare, finance, and autonomous systems exemplify their transformative potential. As these technologies continue to evolve, it is essential to address ethical considerations and ensure that their development aligns with societal values. By harnessing the power of AI and ML responsibly, we can unlock unprecedented opportunities for innovation and improvement in numerous aspects of human life. References Brown, J., & Hagen, A. (2018) “Artificial Intelligence in Financial Services: Risk and Opportunity”. Journal of Financial Technology. 12(3), pp. 45-58. Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) “Dermatologist-Level Classification of Skin Cancer With Deep Neural Networks”. Nature. 542(7639), pp. 115-118. Goodfellow, I., Bengio, Y., & Courville, A. (2016) Deep Learning. MIT Press. Gunning, D. (2017) “Explainable Artificial Intelligence (XAI)”. Defence Advanced Research Projects Agency (DARPA). Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016) “The Ethics of Algorithms: Mapping the Debate”. Big Data & Society. 3(2), pp. 79-105. Russell, S., & Norvig, P. (2020) Artificial Intelligence: A Modern Approach. 4th ed. Pearson.

Basic Algorithms and the Process of Programming an Application

by

In the realm of computer science, algorithms are fundamental constructs that define a sequence of operations to solve specific problems or perform tasks. Understanding basic algorithms and the process of programming an application involves not only writing and optimising these algorithms but also comprehending the roles of various tools in the code generation process. This article delves into the definition of basic algorithms, the relationship between algorithms and code, and the stages involved in programming an application, with a focus on the roles of the pre-processor, compiler, linker, and interpreter. Definition of Basic Algorithms An algorithm is defined as a finite set of well-defined instructions aimed at performing a specific task or solving a problem (Cormen et al., 2009). One classic example of a basic algorithm is the Bubble Sort. Bubble Sort is a simple sorting algorithm that repeatedly steps through the list to be sorted, compares adjacent elements, and swaps them if they are in the wrong order. This process is repeated until the list is sorted. Algorithm: Bubble Sort Start at the beginning of the list. Compare the first two elements. If the first element is greater than the second, swap them. Move to the next pair of elements and repeat the comparison and swap if necessary. Continue this process until the end of the list is reached. Repeat the entire process for the entire list until no swaps are needed. Relationship Between Algorithms and Code The relationship between algorithms and code is intrinsic. Algorithms serve as the blueprint for solving problems, while code is the implementation of these blueprints in a programming language. The process of translating an algorithm into code involves breaking down the algorithm into smaller steps and using the syntax and semantics of a programming language to write instructions that a computer can execute. For instance, the Bubble Sort algorithm can be implemented in Python as follows: python def bubble_sort(arr): n = len(arr) for i in range(n): for j in range(0, n-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j] return arr This code translates the high-level steps of the Bubble Sort algorithm into a sequence of instructions that a computer can follow. The Code Generation Process The process of programming an application involves several stages, each playing a crucial role in transforming high-level code into executable programmes. These stages include pre-processing, compiling, linking, and interpreting. Pre-Processor: The pre-processor is the first stage in the code generation process. It handles directives for source code, such as macro substitution, file inclusion, and conditional compilation. The pre-processor produces an expanded version of the source code, which is then passed to the compiler (Kernighan & Ritchie, 1988). Compiler: The compiler translates the high-level source code into machine code or an intermediate code. It performs syntax analysis, semantic analysis, and optimisations to generate efficient code. The output of the compiler is typically an object file containing machine code (Aho et al., 2006). Linker: The linker combines multiple object files and libraries into a single executable file. It resolves references between object files and assigns final memory addresses to various parts of the programme. The linker ensures that all external references are correctly connected, producing an executable file ready for execution (Louden, 2003). Interpreter: Unlike compilers, interpreters execute code line by line, translating each high-level instruction into machine code on the fly. Interpreters are commonly used in scripting languages and provide immediate feedback during code development (Sebesta, 2016). Understanding basic algorithms and the process of programming an application is essential for any software developer. Algorithms provide the logical foundation for solving problems, while the process of code generation involves several stages, each critical for transforming high-level instructions into executable programmes. By mastering these concepts, developers can write efficient, reliable, and maintainable code. References Aho, A. V., Lam, M. S., Sethi, R., & Ullman, J. D. (2006) Compilers: Principles, Techniques, and Tools (2nd ed.). Addison-Wesley. Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009) Introduction to Algorithms (3rd ed.). MIT Press. Kernighan, B. W., & Ritchie, D. M. (1988) The C Programming Language. 2nd ed. Prentice Hall. Louden, K. C. (2003) Programming Languages: Principles and Practice. 2nd ed. Thomson Learning. Sebesta, R. W. (2016). Concepts of Programming Languages. 11th ed. Pearson.

Computer Science: Overview of Key Topics Within the Field

by

Computer Science is a dynamic and expansive field that encompasses a wide array of topics ranging from theoretical foundations to practical applications. This article provides an overview of some of the key topics within Computer Science, highlighting their significance and interconnections. 1.0 Algorithms and Data Structures Algorithms and data structures form the backbone of computer science, providing methods and tools for solving problems efficiently. An algorithm is a step-by-step procedure for calculations, data processing, and automated reasoning tasks. Data structures, on the other hand, are ways to organise and store data to facilitate efficient access and modification. Knuth’s seminal work, “The Art of Computer Programming,” offers an in-depth exploration of algorithms and data structures, illustrating their fundamental importance in computer science (Knuth, 1997). 2.0 Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and Machine Learning (ML) are pivotal in modern computer science, driving advancements in various domains such as healthcare, finance, and autonomous systems. AI encompasses the development of systems that can perform tasks typically requiring human intelligence, including visual perception, speech recognition, and decision-making. ML, a subset of AI, focuses on the development of algorithms that allow computers to learn from and make predictions based on data. Russell and Norvig’s “Artificial Intelligence: A Modern Approach” is a comprehensive resource that delves into the principles and applications of AI and ML (Russell & Norvig, 2020). 3.0 Computer Networks and the Internet Computer networks, including the Internet, are essential for communication and information exchange in today’s connected world. This topic covers the design, implementation, and management of networks that connect computers and other devices. Key concepts include network protocols, architecture, security, and performance. Kurose and Ross’s “Computer Networking: A Top-Down Approach” provides an extensive overview of how networks operate, from the physical layer to application protocols (Kurose & Ross, 2017). 4.0 Cybersecurity Cybersecurity is the practice of protecting systems, networks, and programs from digital attacks. These attacks are often aimed at accessing, changing, or destroying sensitive information, extorting money from users, or interrupting normal business processes. The field of cybersecurity encompasses various disciplines, including cryptography, network security, and information assurance. Schneier’s “Applied Cryptography” is a foundational text that explores the principles and techniques used to secure data and communication (Schneier, 1996). 5.0 Software Engineering Software engineering involves the application of engineering principles to the development of software. This includes the systematic approach to the design, development, testing, and maintenance of software systems. The goal is to produce high-quality software that is reliable, efficient, and maintainable. Sommerville’s “Software Engineering” is a key reference that outlines best practices and methodologies in the field, from requirements engineering to project management (Sommerville, 2015). 6.0 Human-Computer Interaction Human-Computer Interaction (HCI) studies the design and use of computer technology, focusing particularly on the interfaces between people (users) and computers. Researchers in HCI observe the ways in which humans interact with computers and design technologies that let humans interact with computers in novel ways. The book “Human-Computer Interaction” by Dix et al. provides an in-depth look at the theories, methodologies, and applications of HCI (Dix et al., 2004). 7.0 Database Systems Databases are organised collections of data that are stored and accessed electronically. Database systems provide efficient, reliable, convenient, and safe multi-user storage of and access to massive amounts of persistent data. Silberschatz, Korth, and Sudarshan’s “Database System Concepts” is a comprehensive guide to the fundamental concepts underlying database management systems (Silberschatz et al., 2011). Computer Science is a multifaceted discipline that integrates various fields and concepts, each contributing to the overall advancement of technology and society. Understanding these key topics provides a solid foundation for further exploration and specialisation in the diverse and ever-evolving field of computer science. References Dix, A., Finlay, J., Abowd, G. D., & Beale, R. (2004) Human-Computer Interaction. 3rd ed. Pearson. Knuth, D. E. (1997) The Art of Computer Programming. Vol. 1: Fundamental Algorithms. 3rd ed. Addison-Wesley. Kurose, J. F., & Ross, K. W. (2017) Computer Networking: A Top-Down Approach. 7th ed. Pearson. Russell, S. J., & Norvig, P. (2020) Artificial Intelligence: A Modern Approach. 4th ed. Pearson. Schneier, B. (1996) Applied Cryptography: Protocols, Algorithms, and Source Code in C. 2nd ed. Wiley. Silberschatz, A., Korth, H. F., & Sudarshan, S. (2011) Database System Concepts. 6th ed. McGraw-Hill. Sommerville, I. (2015) Software Engineering. 10th ed. Pearson.

Setting Objectives: Defining SMART Goals for Organisational Success

by

Setting objectives is a fundamental component of strategic management. Objectives act as benchmarks for performance and provide a clear direction for organisational efforts. Without clearly defined goals, organisations risk losing focus, misallocating resources, and underperforming in key areas. The SMART framework—Specific, Measurable, Achievable, Relevant, and Time-bound—is widely adopted for defining effective goals that guide an organisation towards success (Wheelen & Hunger, 2020). This article explores the importance of SMART objectives and how they enhance organisational alignment and performance, offering a strategic tool for achieving both short-term and long-term goals. The Importance of Setting Objectives Objectives are essential for any organisation aiming to achieve its mission and vision. They translate broad strategic goals into specific targets that can be measured and managed. Without objectives, it becomes challenging for an organisation to measure progress or assess performance effectively. By setting clear objectives, organisations ensure that all members understand and work towards common goals, facilitating coordinated efforts across various departments and functions (Drucker, 1954). Moreover, well-defined objectives provide a basis for performance evaluation, helping managers to assess progress and make necessary adjustments to strategies and operations. Peter Drucker (1954), a pioneering thinker in management theory, emphasised that objectives offer clarity and enable focus. Without them, an organisation may find itself without a clear direction, unsure of whether its efforts are aligned with its broader vision. Objectives also play a key role in motivating employees, offering them clear targets and a sense of purpose, which increases their commitment to the organisation’s success. SMART Objectives – Specific Objectives need to be specific to provide a clear focus and direction. A specific objective answers the questions: What needs to be accomplished? Who is responsible for it? What steps need to be taken? For example, rather than setting a vague goal like “increase sales,” a specific objective would be “increase sales of product X by 20% in the North American market by the end of the fiscal year.” This clarity helps employees understand exactly what is expected of them and how their efforts contribute to the broader organisational goals (Locke & Latham, 2002). Specific objectives are easier to communicate and less likely to be misunderstood, ensuring that all stakeholders are aligned in their understanding of what needs to be achieved. Clear, specific objectives also reduce ambiguity and prevent teams from wasting time and resources on tasks that do not contribute to organisational success. When an objective is too broad or unclear, employees may struggle to prioritise tasks or make informed decisions about where to focus their efforts. Specific objectives guide decision-making and provide a foundation for strategic planning and day-to-day operations. SMART Objectives – Measurable Measurable objectives allow organisations to track progress and determine when a goal has been achieved. Metrics and key performance indicators (KPIs) are used to quantify objectives. For instance, if an objective is to “improve customer satisfaction,” a measurable target would be “increase customer satisfaction scores from 85% to 90% within six months.” Measurable objectives provide a concrete way to assess performance, making it easier to identify areas for improvement and celebrate successes (Kaplan & Norton, 1996). By quantifying objectives, organisations can avoid subjective evaluations of performance and instead rely on objective data. This is crucial for ensuring accountability within teams and departments. If progress can be measured, it is easier to make evidence-based decisions, allocate resources more efficiently, and adjust strategies as needed. For example, if sales targets are not being met, managers can investigate factors contributing to underperformance, such as market conditions or internal inefficiencies, and take corrective action. SMART Objectives – Achievable Achievability is crucial to maintaining motivation and commitment. Objectives should be challenging yet realistic, considering the organisation’s resources and constraints. Setting unattainable goals can lead to frustration and demotivation, while setting easily achievable goals may not drive sufficient effort and innovation. An achievable objective strikes a balance, encouraging employees to stretch their capabilities while ensuring the goal is within reach (Locke & Latham, 2006). When objectives are too ambitious, they can have a detrimental effect on organisational morale. Employees who feel that goals are unattainable may lose motivation and reduce their effort, which can undermine overall performance. On the other hand, goals that are too easy to achieve do not inspire innovation or creativity, as employees are not challenged to think critically or develop new approaches. Therefore, it is important for leaders to set objectives that push the organisation forward without overextending its resources or capabilities. SMART Objectives – Relevant Relevant objectives align with the organisation’s mission, vision, and strategic priorities. They should contribute meaningfully to the long-term success of the organisation. For example, a technology company focused on innovation might set an objective to “develop and launch three new software products in the next two years.” This objective is relevant because it supports the company’s strategic focus on innovation and market leadership (Grant, 2016). Ensuring relevance helps maintain organisational focus and prevents resource wastage on inconsequential activities. Relevance is about ensuring that objectives align with broader organisational goals. An objective that does not contribute to the company’s mission is likely to divert resources away from more critical activities. Relevant objectives ensure that every part of the organisation is working towards a common purpose, which increases the overall coherence of strategy implementation. By setting relevant objectives, organisations ensure that their efforts are directed towards achieving meaningful and impactful outcomes. SMART Objectives – Time-bound Time-bound objectives include a clear deadline, creating a sense of urgency and prompting timely action. A time-bound objective specifies when the goal should be achieved, such as “reduce operational costs by 10% within the next 12 months.” Deadlines help in prioritising tasks and enable periodic reviews to assess progress and make adjustments if necessary. Time constraints also prevent goals from being perpetually deferred, ensuring steady progress towards strategic objectives (Kotter, 1996). Without a defined timeframe, objectives can easily become prolonged, leading to delays in project completion or overall stagnation in progress. Time-bound objectives provide a structure for the organisation’s efforts, enabling managers to break … Read more

Six Habits of Happy People: An Exploration of Positive Psychology Principles

by

Happiness has long been a central concern within psychology, philosophy and public health. While early psychological research focused heavily on pathology, the emergence of positive psychology shifted attention towards the strengths, virtues and behaviours that enable individuals to flourish (Seligman and Csikszentmihalyi, 2000). Contemporary research suggests that happiness is not merely a product of circumstance, but is significantly influenced by intentional activities and daily habits (Lyubomirsky, Sheldon and Schkade, 2005). This article critically explores six habits commonly observed among happy people—modesty, mindful communication, lifelong learning, helping the less fortunate, laughter, and ignoring nonsense—demonstrating how each aligns with established psychological theories and empirical findings. 1.0 Don’t Show Off: The Role of Humility and Intrinsic Self-Worth The first habit, not showing off, reflects the psychological value of humility and intrinsic motivation. Individuals who constantly seek external validation may experience unstable self-esteem, as their sense of worth depends upon approval and comparison (Kernis, 2003). In contrast, modest individuals often derive satisfaction from internal standards and meaningful relationships. Lyubomirsky (2008) argues that happiness is enhanced when people pursue intrinsic goals, such as personal growth and connection, rather than extrinsic goals like status or admiration. Self-Determination Theory further supports this claim, proposing that fulfilment arises from satisfying three basic psychological needs: autonomy, competence and relatedness (Deci and Ryan, 2000). For example, an employee who quietly takes pride in mastering new skills may experience deeper and more sustainable wellbeing than someone who constantly seeks recognition for minor achievements. Modesty reduces social comparison, which has been linked to lower life satisfaction when unfavourable (Diener, Emmons, Larsen and Griffin, 1985). Thus, humility fosters stable self-esteem, authentic relationships and internal contentment, all central to lasting happiness. 2.0 Talk Less: Mindfulness and Active Listening The habit of talking less does not imply silence, but rather encourages mindful communication and active listening. Brown and Ryan (2003) define mindfulness as present-moment awareness characterised by openness and non-judgement. Their research demonstrates that mindfulness is positively associated with psychological wellbeing and emotional regulation. Talking less allows space for attentive listening, which strengthens social bonds. Strong interpersonal relationships are consistently among the strongest predictors of happiness (Diener and Seligman, 2002). Active listening fosters empathy, reduces misunderstandings and enhances trust. For instance, in a workplace meeting, an individual who listens carefully rather than dominating conversation is more likely to build collaborative relationships. This aligns with Goleman’s (1995) concept of emotional intelligence, particularly the skills of empathy and social awareness. In this sense, mindful communication cultivates connection, respect and emotional balance, reinforcing overall wellbeing. 3.0 Learn Daily: Growth Mindset and Flow The third habit, learning daily, reflects principles of growth mindset and optimal experience. Dweck (2006) distinguishes between a fixed mindset (believing abilities are static) and a growth mindset (believing abilities can develop). Individuals with a growth mindset demonstrate greater resilience and motivation. Continuous learning stimulates cognitive engagement and provides a sense of mastery. According to Csikszentmihalyi (1990), happiness often arises during states of “flow”—deep absorption in challenging yet manageable tasks. Flow experiences are characterised by concentration, enjoyment and loss of self-consciousness. For example, someone learning a musical instrument may experience flow while practising a new piece. This process fosters not only skill acquisition but also intrinsic satisfaction. Furthermore, lifelong learning supports cognitive health and psychological vitality across the lifespan (WHO, 2022). By nurturing curiosity, individuals cultivate purpose, achievement and adaptability, key components of flourishing. 4.0 Help the Less Fortunate: Altruism and Meaning One of the most robust findings in positive psychology is the link between prosocial behaviour and happiness. Helping others increases life satisfaction and positive affect (Aknin, Dunn and Norton, 2012). Seligman’s (2011) PERMA model identifies meaning and positive relationships as essential pillars of wellbeing. Acts of kindness foster social connection and enhance a sense of purpose. Thoits and Hewitt (2001) found that volunteering is associated with improved mental health and reduced depressive symptoms. Helping the less fortunate shifts focus away from self-preoccupation, promoting gratitude and perspective. For example, volunteering at a local food bank may provide a sense of contribution that surpasses material rewards. Neurobiological research suggests that altruistic acts activate reward centres in the brain, reinforcing positive feelings (Moll et al., 2006). Therefore, altruism strengthens both individual wellbeing and social cohesion, making it a powerful habit of happy people. 5.0 Laugh More: Positive Emotions and Social Bonding Laughter represents a simple yet profound pathway to happiness. Fredrickson’s (2004) broaden-and-build theory proposes that positive emotions expand cognitive and behavioural repertoires, building long-term psychological resources. Laughter reduces physiological stress by lowering cortisol and increasing endorphins (Martin, 2007). It also strengthens social bonds, as shared humour promotes trust and belonging. For example, colleagues who share light-hearted humour during a challenging project may experience reduced tension and improved teamwork. Over time, these moments accumulate into stronger relationships and greater resilience. The NHS (2023) recognises humour and positive interaction as protective factors for mental health. Thus, laughter is not trivial; it is a biopsychosocial mechanism for wellbeing. 6.0 Ignore Nonsense: Emotional Regulation and Cognitive Filtering The final habit, ignoring nonsense, involves the ability to filter trivial negativity and focus on meaningful priorities. Gross (2002) defines emotion regulation as the process by which individuals influence their emotional responses. Effective regulation reduces stress and promotes psychological stability. Cognitive behavioural theory emphasises identifying and challenging unhelpful thoughts (Beck, 2011). By consciously dismissing minor irritations or online negativity, individuals prevent unnecessary emotional escalation. For instance, choosing not to engage in social media arguments preserves emotional energy. This reflects Stoic-inspired principles of focusing only on what lies within one’s control—a concept increasingly integrated into resilience research (Robertson, 2019). Ignoring nonsense therefore protects attention and emotional resources, allowing individuals to maintain clarity, perspective and calmness. 7.0 Interconnectedness of the Six Habits Although discussed separately, these six habits are deeply interconnected. Modesty supports authentic relationships; mindful communication strengthens social bonds; learning fosters competence; helping others enhances meaning; laughter builds resilience; and emotional regulation maintains stability. Together, they align with Seligman’s (2011) PERMA framework—Positive emotion, Engagement, Relationships, Meaning and Achievement. Importantly, happiness is not constant … Read more

Five Key Practices of High-Performing Teams: Insights and Strategies

by

High-performing teams stand out due to their exceptional collaboration, communication, and shared purpose. They demonstrate distinct behaviours that not only enhance productivity but also foster trust, creativity, and engagement. According to Ron Friedman (2021) in the Harvard Business Review, these teams operate differently because they understand that success is built on strong relationships, authentic communication, and purposeful interactions. By focusing on a few deliberate practices, high-performing teams achieve better results, enjoy higher satisfaction, and develop resilience in the face of challenges. This article explores five essential behaviours that characterise high-performing teams — preference for phone calls over digital communication, strategic meeting management, investment in personal relationships, frequent appreciation and recognition, and authenticity and emotional expression — supported by contemporary research, real-world examples, and leadership insights. 1.0 Preference for Phone Calls Over Digital Communication One of the most striking habits of high-performing teams is their preference for phone calls over text-based communication. Research by Friedman (2021) indicates that high-performing teams make up to 66% more phone calls than average teams. This behaviour may seem counterintuitive in a digital age dominated by instant messaging and email, but it reflects an understanding of the limitations of written communication. Phone conversations offer immediacy, warmth, and emotional connection. Unlike written communication, which can be misinterpreted due to lack of tone or context, verbal interactions allow participants to clarify misunderstandings quickly and express empathy through voice cues. Mehrabian’s (1971) communication model** highlights that only 7% of meaning in communication comes from words, while 38% stems from tone and 55% from body language. Although phone calls lack body language, tone still conveys emotional nuances that strengthen relationships and understanding. In practical terms, many remote and hybrid teams have rediscovered the importance of voice communication. For instance, during the COVID-19 pandemic, teams that relied on phone or video calls reported higher psychological safety and connection than those that communicated primarily via text (Leadership Today, 2024). This underscores the value of verbal interactions in maintaining human connection, especially when face-to-face meetings are limited. 2.0 Strategic Meeting Management Another hallmark of high-performing teams is their approach to meeting management. They recognise that not all meetings are productive, and excessive or poorly structured meetings can drain energy and waste time. Instead of reducing the number of meetings, high-performing teams focus on improving meeting quality. According to Leadership Today (2024), such teams conduct 39% more prework than average teams, ensuring that participants arrive prepared. They begin meetings with check-ins — short updates or personal reflections that promote connection and engagement. This practice not only humanises interactions but also sets a collaborative tone. Meetings are structured around clear agendas and outcomes, ensuring alignment between participants and preventing scope creep. This approach reflects Drucker’s (2007) principle of time effectiveness: “There is nothing so useless as doing efficiently what should not be done at all.” By ensuring that meetings are purposeful, inclusive, and results-driven, teams make better decisions and foster shared ownership of outcomes. For example, in companies like Atlassian and Microsoft, meeting effectiveness frameworks are used to promote accountability — participants leave each meeting with assigned actions, timelines, and metrics. This disciplined yet human-centred approach contributes to both efficiency and engagement, ensuring that team time is spent meaningfully. 3.0 Investing in Personal Relationships High-performing teams understand that strong relationships underpin strong performance. They invest in personal connections by engaging in conversations beyond work tasks, discussing interests, families, and life experiences. According to Widdowson and Barbour (2021), these interactions foster trust, empathy, and belonging — essential components of a supportive team culture. This behaviour aligns with Maslow’s (1943) Hierarchy of Needs, which suggests that a sense of belonging is foundational to motivation and performance. When individuals feel valued as people, not just employees, they are more likely to contribute enthusiastically and collaborate effectively. For instance, Google’s Project Aristotle, a landmark study on team performance, found that psychological safety and interpersonal trust were the strongest predictors of team success. Teams that built relationships outside formal work settings — through social events, informal chats, and mutual support — demonstrated higher innovation and satisfaction levels. Simple actions like team lunches, informal coffee chats, or celebrating birthdays help humanise work relationships. These activities transform groups of individuals into cohesive communities that work together toward shared goals. Ultimately, the emotional bonds formed through genuine connection enhance both resilience and collaboration under pressure. 4.0 Frequent Appreciation and Recognition Appreciation and recognition are powerful motivators, and high-performing teams excel at expressing them frequently and sincerely. Research by Widdowson and Barbour (2021) shows that appreciation is not limited to formal rewards but includes informal expressions of gratitude and encouragement. When team members feel seen and valued, they are more engaged, loyal, and productive. Recognition reinforces positive behaviours, boosting morale and strengthening the team’s sense of purpose. According to Herzberg’s (1968) Two-Factor Theory, recognition is one of the most significant motivators in the workplace, enhancing job satisfaction and reducing turnover. Modern organisations such as Salesforce and Deloitte have institutionalised peer recognition systems, enabling employees to acknowledge one another’s contributions in real time. These gestures create a ripple effect of goodwill and support, sustaining a culture of respect and motivation. Moreover, appreciation fosters reciprocity and cooperation. When individuals receive recognition, they are more inclined to extend support and encouragement to others. In essence, a culture of appreciation cultivates psychological safety, making teams more cohesive and engaged. 5.0 Authenticity and Emotional Expression Authenticity is at the heart of trust and effective teamwork. High-performing teams encourage members to express genuine emotions, including frustration or disappointment, without fear of judgement. According to Leadership Today (2022), authenticity fosters emotional openness, allowing teams to address challenges directly and constructively. When individuals feel safe to be themselves, creativity and innovation thrive. Research by Edmondson (2019) on psychological safety demonstrates that teams where members can speak openly about mistakes or concerns are more adaptive and resilient. Suppressing emotions, on the other hand, leads to disengagement and burnout. A case in point is the leadership approach of Satya Nadella, CEO of Microsoft, … Read more

Understanding Austerity: Definition, History, Mechanics, Impact, and Example Case Study

by

Austerity, a term frequently invoked in economic and political discourse, refers to stringent economic policies aimed at reducing government budget deficits through spending cuts, tax increases, or a combination of both. This policy approach, often adopted during periods of economic distress, has been a subject of significant debate among economists, policymakers, and the public. Historical Context and Rationale The concept of austerity is not new. It gained prominence during the Great Depression of the 1930s and was later employed extensively during the debt crises of the 1980s in Latin America and the 1990s in Asia. More recently, it has been a pivotal strategy in the Eurozone crisis following the 2008 global financial meltdown. The rationale behind austerity is rooted in the belief that reducing fiscal deficits and public debt can restore economic stability and foster long-term growth. This perspective is grounded in classical economic theories that advocate for limited government intervention and emphasize the importance of maintaining fiscal discipline (Blanchard et al., 2013). The Mechanics of Austerity Austerity measures typically involve reducing public expenditure on social services, education, and healthcare, alongside increasing taxes. These policies aim to reduce government borrowing and improve fiscal balance. For instance, in Greece, severe austerity measures were implemented as a condition for receiving bailout funds from the International Monetary Fund (IMF) and the European Union (EU). These measures included substantial cuts to pensions, salaries, and public sector jobs, as well as tax hikes (Kentikelenis et al., 2014). Economic and Social Impacts The impacts of austerity are multifaceted and often contentious. Proponents argue that austerity is necessary to curb excessive government debt and avoid the economic instability that can arise from unchecked fiscal deficits. They contend that austerity can lead to increased investor confidence, lower interest rates, and eventually, economic recovery (Alesina & Ardagna, 2010). However, critics highlight the adverse effects of austerity, particularly on vulnerable populations. Austerity measures can lead to higher unemployment, reduced social services, and increased poverty. In the UK, for example, austerity policies implemented in the aftermath of the 2008 financial crisis have been linked to a rise in food bank usage and child poverty rates (Loopstra et al., 2015). Furthermore, austerity can exacerbate economic downturns by reducing aggregate demand, leading to a vicious cycle of economic contraction and fiscal tightening (Blyth, 2013). Austerity in the UK: A Case Study The UK provides a pertinent example of the implementation and consequences of austerity. Following the 2010 general election, the Conservative-led government introduced a series of austerity measures aimed at reducing the fiscal deficit. These included significant cuts to public spending, particularly in welfare, education, and local government funding. According to Taylor-Gooby (2012), these policies were justified on the grounds of reducing the national debt and restoring economic stability. The social repercussions of these policies have been profound. Research by Alston (2018) indicates that austerity has contributed to increased levels of poverty and inequality in the UK. Public services have been strained, with reductions in funding for local councils leading to cuts in social care and other essential services. Moreover, the reduction in welfare benefits has disproportionately affected low-income households, exacerbating economic inequality. Austerity remains a contentious and polarising policy approach. While its proponents argue for the necessity of fiscal discipline and the long-term benefits of reduced debt, critics point to the immediate and often severe social costs. The experiences of countries like Greece and the UK illustrate the complex and often painful trade-offs involved in implementing austerity measures. As policymakers navigate future economic challenges, the debate over austerity’s merits and drawbacks will undoubtedly continue. References Alesina, A., & Ardagna, S. (2010) “Large Changes in Fiscal Policy: Taxes Versus Spending”. In Tax Policy and the Economy. Volume 24, pp. 35-68. University of Chicago Press. Alston, P. (2018) “Statement on Visit to the United Kingdom, By Professor Philip Alston, United Nations Special Rapporteur on Extreme Poverty and Human Rights”. United Nations. [Online]. Available at: https://www.ohchr.org/en/statements/2018/11/statement-visit-united-kingdom-professor-philip-alston-united-nations-special. [Accessed on 17 June 2024]. Blanchard, O., Dell’Ariccia, G., & Mauro, P. (2013) “Rethinking Macro Policy II: Getting Granular. IMF Staff Discussion Note”. International Monetary Fund. [Online]. Available at: https://www.imf.org/external/pubs/ft/sdn/2013/sdn1303.pdf. [Accessed on 17 June 2024]. Blyth, M. (2013) Austerity: The History of a Dangerous Idea. Oxford University Press. Kentikelenis, A., Karanikolos, M., Papanicolas, I., Basu, S., McKee, M., & Stuckler, D. (2014) “Health Effects of Financial Crisis: Omens of a Greek Tragedy”. The Lancet. 383(9918), pp. 748-753. Loopstra, R., Reeves, A., Taylor-Robinson, D., Barr, B., McKee, M., & Stuckler, D. (2015) Austerity, Sanctions, and the Rise of Food Banks in the UK. BMJ. 350, h1775. Taylor-Gooby, P. (2012) “Root and Branch Restructuring to Achieve Major Cuts: The Social Policy Programme of the 2010 UK Coalition Government”. Social Policy & Administration. 46(1), pp.61-82.

About Us
Legal & Compliance