With the growing global interdependence of companies, their scope of responsibility for the environmental, social, and human rights impacts associated with their activities is also growing. In this context, companies are increasingly held accountable for social and ecological issues that lie within the sphere of action of their suppliers and sub-suppliers. They are thus faced with the challenge of meeting these demands for transparency, traceability, and compliance with standards in their Supply Chains (SCs). Based on the theoretical framework of Sustainable Supply Chain Transparency (SSCT) in Sustainable Supply Chain Management (SSCM), this conceptual article aims at initiating the discussion on digitalization in SSCM. Therefore, a heuristical research framework, based on relevant fields in the management of sustainability oriented transparency (governance, cooperation and partner selection, traceability/tracking, and strategic and operational risk assessment) is developed. In relation to these fields, consequently, data-driven digital approaches are identified to which potentials for SSCT and control can be attributed. This initial analysis of existing digital approaches already shows that the market is developing dynamically, but is driven more by individual initiatives. In many cases, the approaches used so far are still in the trial phase or offer only limited solutions. Therefore, this paper contributes by giving an overview of the current application of the digitalization approaches in SSCM pinning our discussion on SSCT dimensions.

Water samples were taken from five sampling points and their quality assessed through analysis of physical and chemical characteristics. Turbidity, temperature, conductivity, pH, dissolved oxygen and total suspended solids were determined on site during sample collection, using potable meters. Anions were determined using UV/Visible spectroscopy while heavy metals were determined using flame Atomic Absorption Spectroscopy (AAS) in accordance with AWWA standard methods. Turbidity was the highest recorded parameter during the wet season with a mean of 481.83 NTU. 53% of the parameters showed significant seasonal variation (P<0.5) with the mean concentration of 56 % of the parameters being higher during the wet season. The parameters that exceeded the WHO limit were turbidity, phosphates, lead, iron, nickel, chromium and cobalt indicating poor quality of water in River Sio. Poor agricultural practices, domestic and industrial wastewater are the main factors that contribute to pollution of the River. The study proposes proper land use, proper treatment and disposal of sewage and use of organic manure and biological control as means of preventing water and soil pollution.

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